Label-Driven Denoising Framework for Multi-Label Few-Shot Aspect Category Detection


Label-Efficient Learning in Agriculture: A Comprehensive Review


Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions


Label-Efficient Multi-Task Segmentation using Contrastive Learning


Label-Efficient Online Continual Object Detection in Streaming Video


Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging


Label-Efficient Semantic Segmentation with Diffusion Models


Label-Enhanced Graph Neural Network for Semi-supervised Node Classification


Label-Free Event-based Object Recognition via Joint Learning with Image Reconstruction from Events


Label-Free Synthetic Pretraining of Object Detectors


Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks


Label-Guided Auxiliary Training Improves 3D Object Detector


Label-Guided In-Context Learning for Named Entity Recognition


Label-Noise Learning with Intrinsically Long-Tailed Data


Label-Only Model Inversion Attacks via Knowledge Transfer


Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels


Label-Synchronous Neural Transducer for E2E Simultaneous Speech Translation


Label-Wise Document Pre-Training for Multi-Label Text Classification


Label-Wise Graph Convolutional Network for Heterophilic Graphs


Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification


Label-aware Hard Negative Sampling Strategies with Momentum Contrastive Learning for Implicit Hate Speech Detection


Label-dependent and event-guided interpretable disease risk prediction using EHRs


Label-efficient Segmentation via Affinity Propagation


Label-efficient Semantic Scene Completion with Scribble Annotations


Label-free Node Classification on Graphs with Large Language Models (LLMS)


Label-wise Aleatoric and Epistemic Uncertainty Quantification


Label2Label: A Language Modeling Framework for Multi-Attribute Learning


LabelAId: Just-in-time AI Interventions for Improving Human Labeling Quality and Domain Knowledge in Crowdsourcing Systems


LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning


LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting


LabelDistill: Label-guided Cross-modal Knowledge Distillation for Camera-based 3D Object Detection


LabelEnc: A New Intermediate Supervision Method for Object Detection


Labeled-to-Unlabeled Distribution Alignment for Partially-Supervised Multi-Organ Medical Image Segmentation


Labeling Chaos to Learning Harmony: Federated Learning with Noisy Labels


Labeling Comic Mischief Content in Online Videos with a Multimodal Hierarchical-Cross-Attention Model


Labeling Messages as AI-Generated Does Not Reduce Their Persuasive Effects


Labeling Neural Representations with Inverse Recognition


Labeling Sentences with Symbolic and Deictic Gestures via Semantic Similarity


Labeling, Cutting, Grouping: an Efficient Text Line Segmentation Method for Medieval Manuscripts


Labelling imaging datasets on the basis of neuroradiology reports: a validation study


Labelling unlabelled videos from scratch with multi-modal self-supervision


Labels Generated by Large Language Model Helps Measuring People's Empathy in Vitro


Labels4Free: Unsupervised Segmentation using StyleGAN


Laboratory Experiments of Model-based Reinforcement Learning for Adaptive Optics Control


Laccolith: Hypervisor-Based Adversary Emulation with Anti-Detection


Lachesis: Scalable Asynchronous BFT on DAG Streams


Lacuna Language Learning: Leveraging RNNs for Ranked Text Completion in Digitized Coptic Manuscripts


Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis


Ladder Fine-tuning approach for SAM integrating complementary network


Ladder Loss for Coherent Visual-Semantic Embedding


Ladder-residual: parallelism-aware architecture for accelerating large model inference with communication overlapping


Ladder: A software to label images, detect objects and deploy models recurrently for object detection


LadderNet: Multi-path networks based on U-Net for medical image segmentation


LadleNet: A Two-Stage UNet for Infrared Image to Visible Image Translation Guided by Semantic Segmentation


Lag Selection for Univariate Time Series Forecasting using Deep Learning: An Empirical Study


Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting


LagKV: Lag-Relative Information of the KV Cache Tells Which Tokens Are Important


Lagged Exact Bayesian Online Changepoint Detection with Parameter Estimation


Lagged teleconnections of climate variables identified via complex rotated Maximum Covariance Analysis


Lagging Inference Networks and Posterior Collapse in Variational Autoencoders


Lagrange Duality and Compound Multi-Attention Transformer for Semi-Supervised Medical Image Segmentation


Lagrange Oscillatory Neural Networks for Constraint Satisfaction and Optimization


Lagrange2D: A Mathematica package for Lagrangian analysis of two-dimensional fluid flows


Lagrangian Gradient Regression for the Detection of Coherent Structures from Sparse Trajectory Data


Lagrangian Manifold Monte Carlo on Monge Patches


Lagrangian Motion Magnification with Double Sparse Optical Flow Decomposition


Lagrangian Neural Style Transfer for Fluids


Lagrangian Objective Function Leads to Improved Unforeseen Attack Generalization in Adversarial Training


Lagrangian Particle Classification and Lagrangian Flux Identities for a Moving Hypersurface


Lagrangian Reachtubes: The Next Generation


Lagrangian Transport Through Surfaces in Compressible Flows


Lagrangian approach for modal analysis of fluid flows


Lagrangian approach to origami vertex analysis: Kinematics


Lagrangian betweenness as a measure of bottlenecks in dynamical systems with oceanographic examples


Lags in the Release, Adoption, and Propagation of npm Vulnerability Fixes


Laguerre-Gauss Preprocessing: Line Profiles as Image Features for Aerial Images Classification


LaiDA: Linguistics-aware In-context Learning with Data Augmentation for Metaphor Components Identification


LakhNES: Improving multi-instrumental music generation with cross-domain pre-training


Lambda Learner: Fast Incremental Learning on Data Streams


Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases


LambdaNet: Probabilistic Type Inference using Graph Neural Networks


LambdaOpt: Learn to Regularize Recommender Models in Finer Levels


LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images


Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networks


LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarks


Lana: A Language-Capable Navigator for Instruction Following and Generation


LancBiO: dynamic Lanczos-aided bilevel optimization via Krylov subspace


Lancaster A at SemEval-2017 Task 5: Evaluation metrics matter: predicting sentiment from financial news headlines


Lanczos with compression for symmetric matrix Lyapunov equations


LanczosNet: Multi-Scale Deep Graph Convolutional Networks


Land Cover Classification from Remote Sensing Images Based on Multi-Scale Fully Convolutional Network


Landau Modes are Eigenmodes of Stellar Systems in the Limit of Zero Collisions


Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model


Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation


Landmark Guided Probabilistic Roadmap Queries


Landmark Management in the Application of Radar SLAM


Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search


Landmark detection in Cardiac Magnetic Resonance Imaging Using A Convolutional Neural Network


Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning


Landmark-free Statistical Shape Modeling via Neural Flow Deformations


LandmarkGAN: Synthesizing Faces from Landmarks


Landmarking 2.0: Bridging the gap between joint models and landmarking


Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models


Landscape More Secure Than Portrait? Zooming Into the Directionality of Digital Images With Security Implications


Landscape of R packages for eXplainable Artificial Intelligence


Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models


Landscape-Sketch-Step: An AI/ML-Based Metaheuristic for Surrogate Optimization Problems


Landslide Topology Uncovers Failure Movements


Landslide mapping from Sentinel-2 imagery through change detection


Lane Change Classification and Prediction with Action Recognition Networks


Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer


Lane Detection using Graph Search and Geometric Constraints for Formula Student Driverless


Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction


LaneAF: Robust Multi-Lane Detection with Affinity Fields


LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving


LaneTCA: Enhancing Video Lane Detection with Temporal Context Aggregation


LangCell: Language-Cell Pre-training for Cell Identity Understanding


LangCoop: Collaborative Driving with Language


LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation


LangGas: Introducing Language in Selective Zero-Shot Background Subtraction for Semi-Transparent Gas Leak Detection with a New Dataset


LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models


LangProp: A code optimization framework using Large Language Models applied to driving


LangSAMP: Language-Script Aware Multilingual Pretraining


LangSplat: 3D Language Gaussian Splatting


LangSuitE: Planning, Controlling and Interacting with Large Language Models in Embodied Text Environments


LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks


LangYa: Revolutionizing Cross-Spatiotemporal Ocean Forecasting


Langevin Autoencoders for Learning Deep Latent Variable Models


Langevin Bi-fidelity Importance Sampling for Failure Probability Estimation


Langevin Flows for Modeling Neural Latent Dynamics


Langevin Incremental Mixture Importance Sampling


Langevin Monte Carlo Beyond Lipschitz Gradient Continuity


Langevin Monte Carlo for Contextual Bandits


Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning


Langevin algorithms for Markovian Neural Networks and Deep Stochastic control


Langevin algorithms for very deep Neural Networks with application to image classification


Langevin diffusions on the torus: estimation and applications


Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient


Langevin equations for landmark image registration with uncertainty


Language Adaptation on a Tight Academic Compute Budget: Tokenizer Swapping Works and Pure bfloat16 Is Enough


Language Adaptive Weight Generation for Multi-task Visual Grounding


Language Agents Meet Causality -- Bridging LLMs and Causal World Models


Language Agnostic Multilingual Information Retrieval with Contrastive Learning


Language Anisotropic Cross-Lingual Model Editing


Language Complexity and Speech Recognition Accuracy: Orthographic Complexity Hurts, Phonological Complexity Doesn't


Language Conditioned Spatial Relation Reasoning for 3D Object Grounding


Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks


Language Detoxification with Attribute-Discriminative Latent Space


Language Embeddings Sometimes Contain Typological Generalizations


Language Embeddings for Typology and Cross-lingual Transfer Learning


Language Fairness in Multilingual Information Retrieval


Language Fusion for Parameter-Efficient Cross-lingual Transfer


Language Generation from Brain Recordings


Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach


Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph


Language Generation with Strictly Proper Scoring Rules


Language Guided Adversarial Purification


Language Guided Concept Bottleneck Models for Interpretable Continual Learning


Language Guided Domain Generalized Medical Image Segmentation


Language Guided Visual Question Answering: Elevate Your Multimodal Language Model Using Knowledge-Enriched Prompts


Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus


Language Identification Using Deep Convolutional Recurrent Neural Networks


Language Identification for Austronesian Languages


Language Independent Neuro-Symbolic Semantic Parsing for Form Understanding


Language Invariant Properties in Natural Language Processing


Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognition


Language Model Adaptation to Specialized Domains through Selective Masking based on Genre and Topical Characteristics


Language Model Alignment with Elastic Reset


Language Model Behavior: A Comprehensive Survey


Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction


Language Model Decoding as Likelihood-Utility Alignment


Language Model Decomposition: Quantifying the Dependency and Correlation of Language Models


Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions


Language Model Guided Interpretable Video Action Reasoning


Language Model Knowledge Distillation for Efficient Question Answering in Spanish


Language Model Powered Digital Biology with BRAD


Language Model Preference Evaluation with Multiple Weak Evaluators


Language Model Prior for Low-Resource Neural Machine Translation


Language Model Sentence Completion with a Parser-Driven Rhetorical Control Method


Language Model Tokenizers Introduce Unfairness Between Languages


Language Model Training Paradigms for Clinical Feature Embeddings


Language Model Uncertainty Quantification with Attention Chain


Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization


Language Model-Based Paired Variational Autoencoders for Robotic Language Learning


Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution


Language Modeling with Editable External Knowledge


Language Modeling with Sparse Product of Sememe Experts


Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling


Language Modelling for Source Code with Transformer-XL


Language Models (Mostly) Do Not Consider Emotion Triggers When Predicting Emotion


Language Models Are Implicitly Continuous


Language Models Are Poor Learners of Directional Inference


Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning


Language Models Can Learn Exceptions to Syntactic Rules


Language Models Can Predict Their Own Behavior


Language Models Can See Better: Visual Contrastive Decoding For LLM Multimodal Reasoning


Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting


Language Models Don't Learn the Physical Manifestation of Language


Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes


Language Models Encode Numbers Using Digit Representations in Base 10


Language Models Encode the Value of Numbers Linearly


Language Models Fail to Introspect About Their Knowledge of Language


Language Models Hallucinate, but May Excel at Fact Verification


Language Models Implement Simple Word2Vec-style Vector Arithmetic


Language Models Learn to Mislead Humans via RLHF


Language Models Meet Anomaly Detection for Better Interpretability and Generalizability


Language Models Meet World Models: Embodied Experiences Enhance Language Models


Language Models Need Inductive Biases to Count Inductively


Language Models Predict Empathy Gaps Between Social In-groups and Out-groups


Language Models Represent Space and Time


Language Models Resist Alignment: Evidence From Data Compression


Language Models Use Monotonicity to Assess NPI Licensing


Language Models are Alignable Decision-Makers: Dataset and Application to the Medical Triage Domain


Language Models are Better Bug Detector Through Code-Pair Classification


Language Models are Few-shot Multilingual Learners


Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding


Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic


Language Models are Realistic Tabular Data Generators


Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch


Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks


Language Models as Black-Box Optimizers for Vision-Language Models


Language Models as Causal Effect Generators


Language Models as Knowledge Bases for Visual Word Sense Disambiguation


Language Models as Knowledge Bases: On Entity Representations, Storage Capacity, and Paraphrased Queries


Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models


Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese


Language Models at the Syntax-Semantics Interface: A Case Study of the Long-Distance Binding of Chinese Reflexive ziji


Language Models can Evaluate Themselves via Probability Discrepancy


Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks


Language Models can Self-Improve at State-Value Estimation for Better Search


Language Models can Self-Lengthen to Generate Long Texts


Language Models can Solve Computer Tasks


Language Models for Code Completion: A Practical Evaluation


Language Models for Code Optimization: Survey, Challenges and Future Directions


Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training


Language Models for Lexical Inference in Context


Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling


Language Models on a Diet: Cost-Efficient Development of Encoders for Closely-Related Languages via Additional Pretraining


Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners


Language Models with Pre-Trained (GloVe) Word Embeddings


Language Models' Factuality Depends on the Language of Inquiry


Language Prior Is Not the Only Shortcut: A Benchmark for Shortcut Learning in VQA


Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages


Language Repository for Long Video Understanding


Language Representation Favored Zero-Shot Cross-Domain Cognitive Diagnosis


Language Representations Can be What Recommenders Need: Findings and Potentials


Language Reward Modulation for Pretraining Reinforcement Learning


Language Semantic Graph Guided Data-Efficient Learning


Language Variety Identification with True Labels


Language Versatilists vs. Specialists: An Empirical Revisiting on Multilingual Transfer Ability


Language and Speech Technology for Central Kurdish Varieties


Language as Queries for Referring Video Object Segmentation


Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generation


Language comparison via network topology


Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification


Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative


Language modeling via stochastic processes


Language models align with human judgments on key grammatical constructions


Language models are better than humans at next-token prediction


Language models are not naysayers: An analysis of language models on negation benchmarks


Language models emulate certain cognitive profiles: An investigation of how predictability measures interact with individual differences


Language models scale reliably with over-training and on downstream tasks


Language with Vision: a Study on Grounded Word and Sentence Embeddings


Language-Agnostic Bias Detection in Language Models with Bias Probing


Language-Agnostic Representation Learning of Source Code from Structure and Context


Language-Agnostic Syllabification with Neural Sequence Labeling


Language-Assisted 3D Feature Learning for Semantic Scene Understanding


Language-Assisted Feature Transformation for Anomaly Detection


Language-Assisted Human Part Motion Learning for Skeleton-Based Temporal Action Segmentation


Language-Aware Multilingual Machine Translation with Self-Supervised Learning


Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation


Language-Based Image Editing with Recurrent Attentive Models


Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation


Language-Codec: Bridging Discrete Codec Representations and Speech Language Models


Language-Conditioned Change-point Detection to Identify Sub-Tasks in Robotics Domains


Language-Conditioned Imitation Learning for Robot Manipulation Tasks


Language-Driven Active Learning for Diverse Open-Set 3D Object Detection


Language-Driven Anchors for Zero-Shot Adversarial Robustness


Language-Driven Dual Style Mixing for Single-Domain Generalized Object Detection


Language-Driven Interactive Shadow Detection


Language-Driven Interactive Traffic Trajectory Generation


Language-Driven Region Pointer Advancement for Controllable Image Captioning


Language-Enhanced Representation Learning for Single-Cell Transcriptomics


Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation


Language-Grounded Indoor 3D Semantic Segmentation in the Wild


Language-Guided Diffusion Model for Visual Grounding


Language-Guided Face Animation by Recurrent StyleGAN-based Generator


Language-Guided Transformer for Federated Multi-Label Classification


Language-Independent Approach for Automatic Computation of Vowel Articulation Features in Dysarthric Speech Assessment


Language-Informed Visual Concept Learning


Language-Model Prior Overcomes Cold-Start Items


Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models


Language-Specific Representation of Emotion-Concept Knowledge Causally Supports Emotion Inference


Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech Recognition


Language-agnostic Topic Classification for Wikipedia


Language-based Image Colorization: A Benchmark and Beyond


Language-biased image classification: evaluation based on semantic representations


Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates


Language-driven Scene Synthesis using Multi-conditional Diffusion Model


Language-free Compositional Action Generation via Decoupling Refinement


Language-guided Human Motion Synthesis with Atomic Actions


Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter


Language-guided Semantic Style Transfer of 3D Indoor Scenes


Language-integrated provenance in Haskell


Languages Transferred Within the Encoder: On Representation Transfer in Zero-Shot Multilingual Translation


LanideNN: Multilingual Language Identification on Character Window


Lanpaint: Training-Free Diffusion Inpainting with Exact and Fast Conditional Inference


Lanthanide molecular nanomagnets as probabilistic bits


LapDDPM: A Conditional Graph Diffusion Model for scRNA-seq Generation with Spectral Adversarial Perturbations


LapGM: A Multisequence MR Bias Correction and Normalization Model


LapGym -- An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery


Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter


LapisGS: Layered Progressive 3D Gaussian Splatting for Adaptive Streaming


Laplace Matching for fast Approximate Inference in Latent Gaussian Models


Laplace Power-expected-posterior priors for generalized linear models with applications to logistic regression


Laplace Redux -- Effortless Bayesian Deep Learning


Laplace Sample Information: Data Informativeness Through a Bayesian Lens


Laplace-HDC: Understanding the geometry of binary hyperdimensional computing


LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification


Laplacian Autoencoders for Learning Stochastic Representations


Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs


Laplacian Flow Dynamics on Geometric Graphs for Anatomical Modeling of Cerebrovascular Networks


Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation


Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification


Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo


Laplacian growth & sandpiles on the Sierpinski gasket: limit shape universality and exact solutions


Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection


Laplacian-based Semi-Supervised Learning in Multilayer Hypergraphs by Coordinate Descent


Laplacian2Mesh: Laplacian-Based Mesh Understanding


LaplacianFusion: Detailed 3D Clothed-Human Body Reconstruction


Lara: Lightweight Anonymous Authentication with Asynchronous Revocation Auditability


Large (Vision) Language Models are Unsupervised In-Context Learners


Large AI Models in Health Informatics: Applications, Challenges, and the Future


Large Arabic Twitter Dataset on COVID-19


Large Batch Simulation for Deep Reinforcement Learning


Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI


Large Data and (Not Even Very) Complex Ecological Models: When Worlds Collide


Large Deviations in Safety-Critical Systems with Probabilistic Initial Conditions


Large Eddy Simulations of Flow over Additively Manufactured Surfaces: Impact of Roughness and Skewness on Turbulent Heat Transfer


Large Engagement Networks for Classifying Coordinated Campaigns and Organic Twitter Trends


Large Foundation Models for Power Systems


Large Graph Signal Denoising with Application to Differential Privacy


Large Images are Gaussians: High-Quality Large Image Representation with Levels of 2D Gaussian Splatting


Large Interferometer For Exoplanets (LIFE). XIV. Finding terrestrial protoplanets in the galactic neighborhood


Large Interferometer For Exoplanets (LIFE): IV. Ideal kernel-nulling array architectures for a space-based mid-infrared nulling interferometer


Large Kernel Distillation Network for Efficient Single Image Super-Resolution


Large Language Model Agent: A Survey on Methodology, Applications and Challenges


Large Language Model Assisted Adversarial Robustness Neural Architecture Search


Large Language Model Augmented Narrative Driven Recommendations


Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval


Large Language Model Can Interpret Latent Space of Sequential Recommender


Large Language Model Can Transcribe Speech in Multi-Talker Scenarios with Versatile Instructions


Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication


Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning


Large Language Model Critics for Execution-Free Evaluation of Code Changes


Large Language Model Distilling Medication Recommendation Model


Large Language Model Enhanced Machine Learning Estimators for Classification


Large Language Model Enhanced Recommender Systems: A Survey


Large Language Model Evaluation via Matrix Nuclear-Norm


Large Language Model Guided Tree-of-Thought


Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective


Large Language Model Instruction Following: A Survey of Progresses and Challenges


Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!


Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement


Large Language Model Recall Uncertainty is Modulated by the Fan Effect


Large Language Model Safety: A Holistic Survey


Large Language Model Unlearning via Embedding-Corrupted Prompts


Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias


Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents


Large Language Model based Multi-Agents: A Survey of Progress and Challenges


Large Language Model for Science: A Study on P vs. NP


Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning


Large Language Model with Region-guided Referring and Grounding for CT Report Generation


Large Language Model-Based Agents for Software Engineering: A Survey


Large Language Model-Brained GUI Agents: A Survey


Large Language Model-Driven Curriculum Design for Mobile Networks


Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation


Large Language Model-Guided Prediction Toward Quantum Materials Synthesis


Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives


Large Language Model-based Decision-making for COLREGs and the Control of Autonomous Surface Vehicles


Large Language Model-based Human-Agent Collaboration for Complex Task Solving


Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network


Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction


Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation


Large Language Models Are Cross-Lingual Knowledge-Free Reasoners


Large Language Models Are Human-Level Prompt Engineers


Large Language Models Are Involuntary Truth-Tellers: Exploiting Fallacy Failure for Jailbreak Attacks


Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning


Large Language Models Are Neurosymbolic Reasoners


Large Language Models Are Not Robust Multiple Choice Selectors


Large Language Models Are Partially Primed in Pronoun Interpretation


Large Language Models Are Reasoning Teachers


Large Language Models Are Semi-Parametric Reinforcement Learning Agents


Large Language Models Are Zero-Shot Time Series Forecasters


Large Language Models Assume People are More Rational than We Really are


Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning


Large Language Models Can Be Easily Distracted by Irrelevant Context


Large Language Models Can Learn Temporal Reasoning


Large Language Models Can Self-Improve At Web Agent Tasks


Large Language Models Enable Few-Shot Clustering


Large Language Models Engineer Too Many Simple Features For Tabular Data


Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review


Large Language Models Meet Contrastive Learning: Zero-Shot Emotion Recognition Across Languages


Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters


Large Language Models Meet Knowledge Graphs for Question Answering: Synthesis and Opportunities


Large Language Models Meet NLP: A Survey


Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPT


Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation


Large Language Models Must Be Taught to Know What They Don't Know


Large Language Models Need Consultants for Reasoning: Becoming an Expert in a Complex Human System Through Behavior Simulation


Large Language Models Need Holistically Thought in Medical Conversational QA


Large Language Models Offer an Alternative to the Traditional Approach of Topic Modelling


Large Language Models Perform Diagnostic Reasoning


Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach


Large Language Models Playing Mixed Strategy Nash Equilibrium Games


Large Language Models Portray Socially Subordinate Groups as More Homogeneous, Consistent with a Bias Observed in Humans


Large Language Models Post-training: Surveying Techniques from Alignment to Reasoning


Large Language Models Produce Responses Perceived to be Empathic


Large Language Models Reflect Human Citation Patterns with a Heightened Citation Bias


Large Language Models Reflect the Ideology of their Creators


Large Language Models Relearn Removed Concepts


Large Language Models Reveal Information Operation Goals, Tactics, and Narrative Frames


Large Language Models Sometimes Generate Purely Negatively-Reinforced Text


Large Language Models Struggle in Token-Level Clinical Named Entity Recognition


Large Language Models Struggle to Learn Long-Tail Knowledge


Large Language Models Synergize with Automated Machine Learning


Large Language Models and Multimodal Retrieval for Visual Word Sense Disambiguation


Large Language Models and Synthetic Data for Monitoring Dataset Mentions in Research Papers


Large Language Models are Autonomous Cyber Defenders


Large Language Models are Better Reasoners with Self-Verification


Large Language Models are Biased Reinforcement Learners


Large Language Models are Built-in Autoregressive Search Engines


Large Language Models are Capable of Offering Cognitive Reappraisal, if Guided


Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales


Large Language Models are Contrastive Reasoners


Large Language Models are Efficient Learners of Noise-Robust Speech Recognition


Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning


Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition


Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples


Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset


Large Language Models are Good Multi-lingual Learners : When LLMs Meet Cross-lingual Prompts


Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners


Large Language Models are Interpretable Learners


Large Language Models are Learnable Planners for Long-Term Recommendation


Large Language Models are Limited in Out-of-Context Knowledge Reasoning


Large Language Models are Locally Linear Mappings


Large Language Models are Near-Optimal Decision-Makers with a Non-Human Learning Behavior


Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization


Large Language Models are Pattern Matchers: Editing Semi-Structured and Structured Documents with ChatGPT


Large Language Models are Pretty Good Zero-Shot Video Game Bug Detectors


Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment


Large Language Models are Temporal and Causal Reasoners for Video Question Answering


Large Language Models are Zero-Shot Rankers for Recommender Systems


Large Language Models are Zero-Shot Reasoners


Large Language Models are biased to overestimate profoundness


Large Language Models are few(1)-shot Table Reasoners


Large Language Models are not Fair Evaluators


Large Language Models as Attribution Regularizers for Efficient Model Training


Large Language Models as Carriers of Hidden Messages


Large Language Models as Corporate Lobbyists


Large Language Models as Evaluators for Recommendation Explanations


Large Language Models as Evolutionary Optimizers


Large Language Models as Interpolated and Extrapolated Event Predictors


Large Language Models as Planning Domain Generators


Large Language Models as Realistic Microservice Trace Generators


Large Language Models as Sous Chefs: Revising Recipes with GPT-3


Large Language Models as Surrogate Models in Evolutionary Algorithms: A Preliminary Study


Large Language Models as Zero-Shot Conversational Recommenders


Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical Study


Large Language Models as Zero-shot Dialogue State Tracker through Function Calling


Large Language Models can Contrastively Refine their Generation for Better Sentence Representation Learning


Large Language Models can Strategically Deceive their Users when Put Under Pressure


Large Language Models can be Guided to Evade AI-Generated Text Detection


Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning


Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey


Large Language Models for Automated Open-domain Scientific Hypotheses Discovery


Large Language Models for Code Analysis: Do LLMs Really Do Their Job?


Large Language Models for Code Generation: The Practitioners Perspective


Large Language Models for Computer-Aided Design: A Survey


Large Language Models for Constrained-Based Causal Discovery


Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey


Large Language Models for Controllable Multi-property Multi-objective Molecule Optimization


Large Language Models for Cross-lingual Emotion Detection


Large Language Models for Data Synthesis


Large Language Models for Depression Recognition in Spoken Language Integrating Psychological Knowledge


Large Language Models for Expansion of Spoken Language Understanding Systems to New Languages


Large Language Models for Explainable Decisions in Dynamic Digital Twins


Large Language Models for Failure Mode Classification: An Investigation


Large Language Models for Financial Aid in Financial Time-series Forecasting


Large Language Models for Generative Information Extraction: A Survey


Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming


Large Language Models for Information Retrieval: A Survey


Large Language Models for Ingredient Substitution in Food Recipes using Supervised Fine-tuning and Direct Preference Optimization


Large Language Models for Integrating Social Determinant of Health Data: A Case Study on Heart Failure 30-Day Readmission Prediction


Large Language Models for Intent-Driven Session Recommendations


Large Language Models for Multi-Robot Systems: A Survey


Large Language Models for Multilingual Previously Fact-Checked Claim Detection


Large Language Models for Multilingual Vulnerability Detection: How Far Are We?


Large Language Models for Multimodal Deformable Image Registration


Large Language Models for Networking: Applications, Enabling Techniques, and Challenges


Large Language Models for Next Point-of-Interest Recommendation


Large Language Models for Orchestrating Bimanual Robots


Large Language Models for Outpatient Referral: Problem Definition, Benchmarking and Challenges


Large Language Models for Planning: A Comprehensive and Systematic Survey


Large Language Models for Power Scheduling: A User-Centric Approach


Large Language Models for Propaganda Span Annotation


Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Field


Large Language Models for Scientific Synthesis, Inference and Explanation


Large Language Models for Software Engineering: A Systematic Literature Review


Large Language Models for Test-Free Fault Localization


Large Language Models for Time Series: A Survey


Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages


Large Language Models for Validating Network Protocol Parsers


Large Language Models for the Automated Analysis of Optimization Algorithms


Large Language Models in Computer Science Education: A Systematic Literature Review


Large Language Models in Fault Localisation


Large Language Models in the Clinic: A Comprehensive Benchmark


Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System


Large Language Models of Code Fail at Completing Code with Potential Bugs


Large Language Models on Graphs: A Comprehensive Survey


Large Language Models on Small Resource-Constrained Systems: Performance Characterization, Analysis and Trade-offs


Large Language Models on Wikipedia-Style Survey Generation: an Evaluation in NLP Concepts


Large Language Models to Identify Social Determinants of Health in Electronic Health Records


Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey


Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation


Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors


Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning


Large Language Monkeys: Scaling Inference Compute with Repeated Sampling


Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models


Large Legislative Models: Towards Efficient AI Policymaking in Economic Simulations


Large Margin Softmax Loss for Speaker Verification


Large Model Empowered Streaming Speech Semantic Communications


Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook


Large Multi-modal Models Can Interpret Features in Large Multi-modal Models


Large Multi-modality Model Assisted AI-Generated Image Quality Assessment


Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages


Large Neighborhood Prioritized Search for Combinatorial Optimization with Answer Set Programming


Large Neighborhood Search based on Neural Construction Heuristics


Large Norms of CNN Layers Do Not Hurt Adversarial Robustness


Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression


Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Do


Large Pre-trained time series models for cross-domain Time series analysis tasks


Large Raw Emotional Dataset with Aggregation Mechanism


Large Sample Properties of Entropy Balancing Estimators of Average Causal Effects


Large Sample Properties of Partitioning-Based Series Estimators


Large Scale Clustering with Variational EM for Gaussian Mixture Models


Large Scale Correlation Clustering Optimization


Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior


Large Scale Font Independent Urdu Text Recognition System


Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity


Large Scale Holistic Video Understanding


Large Scale Image Completion via Co-Modulated Generative Adversarial Networks


Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods


Large Scale MRI Collection and Segmentation of Cirrhotic Liver


Large Scale Multi-GPU Based Parallel Traffic Simulation for Accelerated Traffic Assignment and Propagation


Large Scale Multi-Lingual Multi-Modal Summarization Dataset


Large Scale Multimodal Classification Using an Ensemble of Transformer Models and Co-Attention


Large Scale Open-Set Deep Logo Detection


Large Scale Transfer Learning for Tabular Data via Language Modeling


Large Self-Supervised Models Bridge the Gap in Domain Adaptive Object Detection


Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in CNN


Large Spatial Model: End-to-end Unposed Images to Semantic 3D


Large Synthetic Data from the arXiv for OCR Post Correction of Historic Scientific Articles


Large Vision-Language Models for Knowledge-Grounded Data Annotation of Memes


Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks


Large Wireless Model (LWM): A Foundation Model for Wireless Channels


Large area optimization of meta-lens via data-free machine learning


Large data limit of the MBO scheme for data clustering: $Γ$-convergence of the thresholding energies


Large deviation full counting statistics in adiabatic open quantum dynamics


Large deviations of extreme eigenvalues of generalized sample covariance matrices


Large language model for Bible sentiment analysis: Sermon on the Mount


Large language model validity via enhanced conformal prediction methods


Large language models are good medical coders, if provided with tools


Large language models as oracles for instantiating ontologies with domain-specific knowledge


Large language models can be zero-shot anomaly detectors for time series?


Large language models can consistently generate high-quality content for election disinformation operations


Large language models effectively leverage document-level context for literary translation, but critical errors persist


Large language models for aspect-based sentiment analysis


Large language models for newspaper sentiment analysis during COVID-19: The Guardian


Large language models surpass human experts in predicting neuroscience results


Large model enhanced computational ghost imaging


Large network community detection by fast label propagation


Large population limit for a multilayer SIR model including households and workplaces


Large problems are not necessarily hard: A case study on distributed NMPC paying off


Large sample spectral analysis of graph-based multi-manifold clustering


Large scale evaluation of local image feature detectors on homography datasets


Large scale modeling of antimicrobial resistance with interpretable classifiers


Large scale multi-node simulations of $\mathbb{Z}_2$ gauge theory quantum circuits using Google Cloud Platform


Large scale traffic forecasting with gradient boosting, Traffic4cast 2022 challenge


Large scale visual place recognition with sub-linear storage growth


Large width penalization for neural network-based prediction interval estimation


Large, Complex, and Realistic Safety Clothing and Helmet Detection: Dataset and Method


Large-Angle Convergent-Beam Electron Diffraction Patterns via Conditional Generative Adversarial Networks


Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization


Large-Margin Classification in Hyperbolic Space


Large-Scale 3D Medical Image Pre-training with Geometric Context Priors


Large-Scale Approximate k-NN Graph Construction on GPU


Large-Scale Bidirectional Training for Zero-Shot Image Captioning


Large-Scale Characterization and Segmentation of Internet Path Delays with Infinite HMMs


Large-Scale Cover Song Detection in Digital Music Libraries Using Metadata, Lyrics and Audio Features


Large-Scale Differentiable Causal Discovery of Factor Graphs


Large-Scale Electron Microscopy Image Segmentation in Spark


Large-Scale Evaluation of Topic Models and Dimensionality Reduction Methods for 2D Text Spatialization


Large-Scale GNSS Spreading Code Optimization


Large-Scale Gaussian Processes via Alternating Projection


Large-Scale Graphs Community Detection using Spark GraphFrames


Large-Scale Hate Speech Detection with Cross-Domain Transfer


Large-Scale Hyperspectral Image Clustering Using Contrastive Learning


Large-Scale Knowledge Integration for Enhanced Molecular Property Prediction


Large-Scale Learnable Graph Convolutional Networks


Large-Scale Learning with Fourier Features and Tensor Decompositions


Large-Scale Methods for Distributionally Robust Optimization


Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning


Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework


Large-Scale Multi-Hypotheses Cell Tracking Using Ultrametric Contours Maps


Large-Scale Multi-Robot Assembly Planning for Autonomous Manufacturing


Large-Scale Multi-omic Biosequence Transformers for Modeling Protein-Nucleic Acid Interactions


Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity


Large-Scale Open-Set Classification Protocols for ImageNet


Large-Scale Parallel Matching of Social Network Profiles


Large-Scale Pre-training for Person Re-identification with Noisy Labels


Large-Scale Pretraining and Finetuning for Efficient Jet Classification in Particle Physics


Large-Scale Representation Learning on Graphs via Bootstrapping


Large-Scale Scenarios of Electric Vehicle Charging with a Data-Driven Model of Control


Large-Scale Spatio-Temporal Person Re-identification: Algorithms and Benchmark


Large-Scale Stochastic Sampling from the Probability Simplex


Large-Scale Study of Temporal Shift in Health Insurance Claims


Large-Scale Subspace Clustering via k-Factorization


Large-Scale Targeted Cause Discovery with Data-Driven Learning


Large-Scale Topological Radar Localization Using Learned Descriptors


Large-Scale Traffic Congestion Prediction based on Multimodal Fusion and Representation Mapping


Large-Scale Unsupervised Object Discovery


Large-Scale Weakly Labeled Semi-Supervised Sound Event Detection in Domestic Environments


Large-Scale and Multi-Perspective Opinion Summarization with Diverse Review Subsets


Large-Scale-Exploit of GitHub Repository Metadata and Preventive Measures


Large-Scale-Fading Decoding in Cellular Massive MIMO Systems with Spatially Correlated Channels


Large-Z atoms in the strong-interaction limit of DFT: Implications for gradient expansions and for the Lieb-Oxford bound


Large-batch Optimization for Dense Visual Predictions


Large-capacity and Flexible Video Steganography via Invertible Neural Network


Large-displacement 3D Object Tracking with Hybrid Non-local Optimization


Large-image Object Detection for Fine-grained Recognition of Punches Patterns in Medieval Panel Painting


Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation


Large-sample analysis of cost functionals for inference under the coalescent


Large-scale Artificial Neural Network: MapReduce-based Deep Learning


Large-scale Bayesian Structure Learning for Gaussian Graphical Models using Marginal Pseudo-likelihood


Large-scale Bilingual Language-Image Contrastive Learning


Large-scale Building Damage Assessment using a Novel Hierarchical Transformer Architecture on Satellite Images


Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation


Large-scale Data Integration using Matrix Denoising and Geometric Factor Matching


Large-scale Dataset Pruning with Dynamic Uncertainty


Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding


Large-scale Environmental Data Science with ExaGeoStatR


Large-scale Evaluation of Transformer-based Article Encoders on the Task of Citation Recommendation


Large-scale Hierarchical Alignment for Data-driven Text Rewriting


Large-scale Long-tailed Disease Diagnosis on Radiology Images


Large-scale Maps of the Cosmic Infrared Background from Planck


Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey


Large-scale Multi-granular Concept Extraction Based on Machine Reading Comprehension


Large-scale Multi-layer Academic Networks Derived from Statistical Publications


Large-scale Multi-view Subspace Clustering in Linear Time


Large-scale Neural Solvers for Partial Differential Equations


Large-scale Optimization with Linear Equality Constraints using Reduced Compact Representation


Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network


Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery


Large-scale Pre-training for Grounded Video Caption Generation


Large-scale Ridesharing DARP Instances Based on Real Travel Demand


Large-scale Robustness Analysis of Video Action Recognition Models


Large-scale School Mapping using Weakly Supervised Deep Learning for Universal School Connectivity


Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence


Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding


Large-scale benchmark study of survival prediction methods using multi-omics data


Large-scale cloze evaluation reveals that token prediction tasks are neither lexically nor semantically aligned


Large-scale flood modeling and forecasting with FloodCast


Large-scale holographic particle 3D imaging with the beam propagation model


Large-scale image segmentation based on distributed clustering algorithms


Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks


Large-scale machine learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology


Large-scale multi-objective influence maximisation with network downscaling


Large-scale neural recordings call for new insights to link brain and behavior


Large-scale optimal transport map estimation using projection pursuit


Large-scale power loss in ground-based CMB mapmaking


Large-scale pretraining on pathological images for fine-tuning of small pathological benchmarks


Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT


Large-scale quantum approximate optimization on non-planar graphs with machine learning noise mitigation


Large-scale quantum reservoir learning with an analog quantum computer


Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively


Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks


Large-scale, Language-agnostic Discourse Classification of Tweets During COVID-19


Large-to-small Image Resolution Asymmetry in Deep Metric Learning


Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning


LargeEA: Aligning Entities for Large-scale Knowledge Graphs


LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs


LargeNetVis: Visual Exploration of Large Temporal Networks Based on Community Taxonomies


LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting


Larger Language Models Don't Care How You Think: Why Chain-of-Thought Prompting Fails in Subjective Tasks


Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation


Larger-scale Nakamoto-style Blockchains Don't Necessarily Offer Better Security


Larimar: Large Language Models with Episodic Memory Control


Larth: Dataset and Machine Translation for Etruscan


LasHeR: A Large-scale High-diversity Benchmark for RGBT Tracking


Lasagna: Layered Score Distillation for Disentangled Object Relighting


Laser Frequency Noise in Next Generation Gravitational-Wave Detectors


Laser Learning Environment: A new environment for coordination-critical multi-agent tasks


Laser-induced alignment of nanoparticles and macromolecules for single-particle-imaging applications


Laser: Efficient Language-Guided Segmentation in Neural Radiance Fields


LaserEscape: Detecting and Mitigating Optical Probing Attacks


LaserHuman: Language-guided Scene-aware Human Motion Generation in Free Environment


Lasso Gripper: A String Shooting-Retracting Mechanism for Shape-Adaptive Grasping


Lasso Regularization Paths for NARMAX Models via Coordinate Descent


LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso


Last Layer Marginal Likelihood for Invariance Learning


Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations


Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities


Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games


Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks


Last-Level Cache Side-Channel Attacks Are Feasible in the Modern Public Cloud (Extended Version)


LastResort at SemEval-2024 Task 3: Exploring Multimodal Emotion Cause Pair Extraction as Sequence Labelling Task


LatEval: An Interactive LLMs Evaluation Benchmark with Incomplete Information from Lateral Thinking Puzzles


Late Breaking Result: FPGA-Based Emulation and Fault Injection for CNN Inference Accelerators


Late Fusion Multi-view Clustering via Global and Local Alignment Maximization


Late Prompt Tuning: A Late Prompt Could Be Better Than Many Prompts


Late Stopping: Avoiding Confidently Learning from Mislabeled Examples


Late Temporal Modeling in 3D CNN Architectures with BERT for Action Recognition


Late time approaches to the Hubble tension deforming $H(z)$, worsen the growth tension


Latency Optimization for Wireless Federated Learning in Multihop Networks


Latency-aware Spatial-wise Dynamic Networks


Latent Alignment and Variational Attention


Latent Alignment of Procedural Concepts in Multimodal Recipes


Latent Aspect Detection from Online Unsolicited Customer Reviews


Latent Bottlenecked Attentive Neural Processes


Latent CLAP Loss for Better Foley Sound Synthesis


Latent Chain-of-Thought? Decoding the Depth-Recurrent Transformer


Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering


Latent Concept-based Explanation of NLP Models


Latent Degradation Representation Constraint for Single Image Deraining


Latent Denoising Diffusion GAN: Faster sampling, Higher image quality


Latent Diffeomorphic Dynamic Mode Decomposition


Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel Noises


Latent Diffusion Prior Enhanced Deep Unfolding for Snapshot Spectral Compressive Imaging


Latent Diffusion U-Net Representations Contain Positional Embeddings and Anomalies


Latent Diffusion for Language Generation


Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracy


Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing Images


Latent Dirichlet Analysis of Categorical Survey Responses


Latent Discriminant deterministic Uncertainty


Latent Disentanglement in Mesh Variational Autoencoders Improves the Diagnosis of Craniofacial Syndromes and Aids Surgical Planning


Latent Distance Estimation for Random Geometric Graphs


Latent Distillation for Continual Object Detection at the Edge


Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification


Latent Execution for Neural Program Synthesis


Latent Exploration for Reinforcement Learning


Latent Feature Relation Consistency for Adversarial Robustness


Latent Feature and Attention Dual Erasure Attack against Multi-View Diffusion Models for 3D Assets Protection


Latent Feature-based Data Splits to Improve Generalisation Evaluation: A Hate Speech Detection Case Study


Latent Field Discovery In Interacting Dynamical Systems With Neural Fields


Latent Fingerprint Matching via Dense Minutia Descriptor


Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data


Latent Gaussian and Hüsler--Reiss Graphical Models with Golazo Penalty


Latent Guard: a Safety Framework for Text-to-image Generation


Latent Guided Sampling for Combinatorial Optimization


Latent Hatred: A Benchmark for Understanding Implicit Hate Speech


Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing


Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing


Latent Iterative Refinement for Modular Source Separation


Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models


Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization


Latent Modes of Nonlinear Flows -- a Koopman Theory Analysis


Latent Modulated Function for Computational Optimal Continuous Image Representation


Latent Multi-view Semi-Supervised Classification


Latent Multimodal Reconstruction for Misinformation Detection


Latent Network Estimation and Variable Selection for Compositional Data via Variational EM


Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data


Latent Network Summarization: Bridging Network Embedding and Summarization


Latent Neural Differential Equations for Video Generation


Latent Neural ODEs with Sparse Bayesian Multiple Shooting


Latent Neural Operator for Solving Forward and Inverse PDE Problems


Latent Neural Stochastic Differential Equations for Change Point Detection


Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping


Latent Normalizing Flows for Discrete Sequences


Latent Normalizing Flows for Many-to-Many Cross-Domain Mappings


Latent Outlier Exposure for Anomaly Detection with Contaminated Data


Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models


Latent Partition Implicit with Surface Codes for 3D Representation


Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference


Latent Predictor Networks for Code Generation


Latent Processes Identification From Multi-View Time Series


Latent Prototype Routing: Achieving Near-Perfect Load Balancing in Mixture-of-Experts


Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic Material


Latent Retrieval for Weakly Supervised Open Domain Question Answering


Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning


Latent Semantic Consensus For Deterministic Geometric Model Fitting


Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI


Latent Similarity Identifies Important Functional Connections for Phenotype Prediction


Latent Space Autoregression for Novelty Detection


Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation


Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification


Latent Space Factorisation and Manipulation via Matrix Subspace Projection


Latent Space Representations of Neural Algorithmic Reasoners


Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation


Latent Space Smoothing for Individually Fair Representations


Latent Space Super-Resolution for Higher-Resolution Image Generation with Diffusion Models


Latent Space Translation via Semantic Alignment


Latent Space is Feature Space: Regularization Term for GANs Training on Limited Dataset


Latent Spaces Enable Transformer-Based Dose Prediction in Complex Radiotherapy Plans


Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation


Latent Structure in Collaboration: the Case of Reddit r/place


Latent Structured Hopfield Network for Semantic Association and Retrieval


Latent Structures of Intertextuality in French Fiction


Latent Subgroup Identification in Image-on-scalar Regression


Latent Thermodynamic Flows: Unified Representation Learning and Generative Modeling of Temperature-Dependent Behaviors from Limited Data


Latent Transformations via NeuralODEs for GAN-based Image Editing


Latent Traversals in Generative Models as Potential Flows


Latent Tree Learning with Ordered Neurons: What Parses Does It Produce?


Latent Variable Method Demonstrator -- Software for Understanding Multivariate Data Analytics Algorithms


Latent Variable Model for Multi-modal Translation


Latent Variable Modelling with Hyperbolic Normalizing Flows


Latent Variable Multi-output Gaussian Processes for Hierarchical Datasets


Latent Variable Sequence Identification for Cognitive Models with Neural Network Estimators


Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction


Latent Variable Time-varying Network Inference


Latent Video Diffusion Models for High-Fidelity Long Video Generation


Latent Watermark: Inject and Detect Watermarks in Latent Diffusion Space


Latent World Models For Intrinsically Motivated Exploration


Latent assimilation with implicit neural representations for unknown dynamics


Latent common manifold learning with alternating diffusion: analysis and applications


Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification


Latent geometry and dynamics of proximity networks


Latent process models for functional network data


Latent space approaches to aggregate network data


Latent space representation for multi-target speaker detection and identification with a sparse dataset using Triplet neural networks


Latent structure blockmodels for Bayesian spectral graph clustering


Latent variable model for high-dimensional point process with structured missingness


Latent-KalmanNet: Learned Kalman Filtering for Tracking from High-Dimensional Signals


Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures


Latent-OFER: Detect, Mask, and Reconstruct with Latent Vectors for Occluded Facial Expression Recognition


Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection


Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds


Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior


Latent-based Diffusion Model for Long-tailed Recognition


Latent-space disentanglement with untrained generator networks for the isolation of different motion types in video data


LatentAugment: Data Augmentation via Guided Manipulation of GAN's Latent Space


LatentAugment: Dynamically Optimized Latent Probabilities of Data Augmentation


LatentBKI: Open-Dictionary Continuous Mapping in Visual-Language Latent Spaces with Quantifiable Uncertainty


LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration


LatentEditor: Text Driven Local Editing of 3D Scenes


LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models


LatentGNN: Learning Efficient Non-local Relations for Visual Recognition


LatentGaze: Cross-Domain Gaze Estimation through Gaze-Aware Analytic Latent Code Manipulation


LatentMan: Generating Consistent Animated Characters using Image Diffusion Models


LatentPoison - Adversarial Attacks On The Latent Space


LatentSwap: An Efficient Latent Code Mapping Framework for Face Swapping


Lateralization MLP: A Simple Brain-inspired Architecture for Diffusion


LatestEval: Addressing Data Contamination in Language Model Evaluation through Dynamic and Time-Sensitive Test Construction


Latexify Math: Mathematical Formula Markup Revision to Assist Collaborative Editing in Math Q&A Sites


Latin BERT: A Contextual Language Model for Classical Philology


Latin Treebanks in Review: An Evaluation of Morphological Tagging Across Time


Latin writing styles analysis with Machine Learning: New approach to old questions


Latitude Quenching Nonlinearity in the Solar Dynamo


Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models


LatteGAN: Visually Guided Language Attention for Multi-Turn Text-Conditioned Image Manipulation


LatteReview: A Multi-Agent Framework for Systematic Review Automation Using Large Language Models


Lattice $φ^{4}$ field theory as a multi-agent system of financial markets


Lattice Boltzmann Benchmark Kernels as a Testbed for Performance Analysis


Lattice Climber Attack: Adversarial attacks for randomized mixtures of classifiers


Lattice Experiments using Fermionic Operators and the Variational Eigensolver in a Quantum Computer


Lattice Green's Functions for High Order Finite Difference Stencils


Lattice Multislice Algorithm for Fast Simulation of Scanning Transmission Electron Microscopy Images


Lattice Surgery Translation for Quantum Computation


Lattice dynamics of quasi-2D perovskites from first-principles


Lattice paths and submonoids of $\mathbb Z^2$


Lattice strain measurement of core@shell electrocatalysts with 4D-STEM nanobeam electron diffraction


Lattice studies of the $Sp(4)$ gauge theory with two fundamental and three antisymmetric Dirac fermions


Lattice-Constant and Band-Gap Tuning in Wurtzite and Zincblende BInGaN Alloys


Lattice-based stochastic models motivate non-linear diffusion descriptions of memory-based dispersal


Lattice-preserving $\mathcal{ALC}$ ontology embeddings with saturation


LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud


LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data


Latxa: An Open Language Model and Evaluation Suite for Basque


Laugh Now Cry Later: Controlling Time-Varying Emotional States of Flow-Matching-Based Zero-Shot Text-to-Speech


Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?


Laughing Matters: Introducing Laughing-Face Generation using Diffusion Models


Laughter Synthesis using Pseudo Phonetic Tokens with a Large-scale In-the-wild Laughter Corpus


Laughter Synthesis: Combining Seq2seq modeling with Transfer Learning


Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python


LaunchpadGPT: Language Model as Music Visualization Designer on Launchpad


LauraTSE: Target Speaker Extraction using Auto-Regressive Decoder-Only Language Models


Law Article-Enhanced Legal Case Matching: a Causal Learning Approach


Law of the Weakest Link: Cross Capabilities of Large Language Models


Law on the Market? Abnormal Stock Returns and Supreme Court Decision-Making


LawBench: Benchmarking Legal Knowledge of Large Language Models


LawDNet: Enhanced Audio-Driven Lip Synthesis via Local Affine Warping Deformation


LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM


Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents


Lawful and Accountable Personal Data Processing with GDPR-based Access and Usage Control in Distributed Systems


LawngNLI: A Long-Premise Benchmark for In-Domain Generalization from Short to Long Contexts and for Implication-Based Retrieval


Lay-A-Scene: Personalized 3D Object Arrangement Using Text-to-Image Priors


LayAlign: Enhancing Multilingual Reasoning in Large Language Models via Layer-Wise Adaptive Fusion and Alignment Strategy


Layer 2 be or Layer not 2 be: Scaling on Uniswap v3


Layer Adaptive Deep Neural Networks for Out-of-distribution Detection


Layer Folding: Neural Network Depth Reduction using Activation Linearization


Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training


Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations


Layer Potential Methods for Doubly-Periodic Harmonic Functions


Layer Pruning with Consensus: A Triple-Win Solution


Layer formation and relaminarisation in plane Couette flow with spanwise stratification


Layer or Representation Space: What makes BERT-based Evaluation Metrics Robust?


Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency


Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks


Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense


Layer-Parallel Training of Deep Residual Neural Networks


Layer-Wise Feature Metric of Semantic-Pixel Matching for Few-Shot Learning


Layer-Wise Quantization: A Pragmatic and Effective Method for Quantizing LLMs Beyond Integer Bit-Levels


Layer-adaptive sparsity for the Magnitude-based Pruning


Layer-wise Auto-Weighting for Non-Stationary Test-Time Adaptation


Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models


Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework


LayerAct: Advanced Activation Mechanism for Robust Inference of CNNs


LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation


LayerDropBack: A Universally Applicable Approach for Accelerating Training of Deep Networks


LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging


LayerMix: Enhanced Data Augmentation through Fractal Integration for Robust Deep Learning


LayerPlexRank: Exploring Node Centrality and Layer Influence through Algebraic Connectivity in Multiplex Networks


LayerShuffle: Enhancing Robustness in Vision Transformers by Randomizing Layer Execution Order


LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding


LayerTracer: Cognitive-Aligned Layered SVG Synthesis via Diffusion Transformer


Layered Embeddings for Amodal Instance Segmentation


Layered Models can "Automatically" Regularize and Discover Low-Dimensional Structures via Feature Learning


Layered Unlearning for Adversarial Relearning


Layered and Staged Monte Carlo Tree Search for SMT Strategy Synthesis


LayeredDoc: Domain Adaptive Document Restoration with a Layer Separation Approach


Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning


Layerwise Recurrent Router for Mixture-of-Experts


Layerwise Relevance Visualization in Convolutional Text Graph Classifiers


Laying Anchors: Semantically Priming Numerals in Language Modeling


Laying foundations to quantify the "Effort of Reproducibility"


Layout Generation Agents with Large Language Models


Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering


Layout-Guided Novel View Synthesis from a Single Indoor Panorama


Layout-aware Dreamer for Embodied Referring Expression Grounding


Layout-to-Image Translation with Double Pooling Generative Adversarial Networks


LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designer


LayoutDM: Discrete Diffusion Model for Controllable Layout Generation


LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation


LayoutEnhancer: Generating Good Indoor Layouts from Imperfect Data


LayoutGPT: Compositional Visual Planning and Generation with Large Language Models


LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding


LayoutMP3D: Layout Annotation of Matterport3D


LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models


Lazarus Stars: Numerical investigations of stellar evolution with star-lifting as a life extension strategy


Lazy Data Practices Harm Fairness Research


Lazy Estimation of Variable Importance for Large Neural Networks


Lazy FSCA for Unsupervised Variable Selection


Lazy Reimplication in Chronological Backtracking


Lazy and Fast Greedy MAP Inference for Determinantal Point Process


Lazy stochastic principal component analysis


Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty


Lazy-DaSH: Lazy Approach for Hypergraph-based Multi-robot Task and Motion Planning


Lazy-k: Decoding for Constrained Token Classification


LazyFox: Fast and parallelized overlapping community detection in large graphs


LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation


LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments


LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews


LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models


LeGEND: A Top-Down Approach to Scenario Generation of Autonomous Driving Systems Assisted by Large Language Models


LeGO: Leveraging a Surface Deformation Network for Animatable Stylized Face Generation with One Example


LeGrad: An Explainability Method for Vision Transformers via Feature Formation Sensitivity


LeMON: Learning to Learn Multi-Operator Networks


LeMeViT: Efficient Vision Transformer with Learnable Meta Tokens for Remote Sensing Image Interpretation


LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos


LeMoRe: Learn More Details for Lightweight Semantic Segmentation


LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation


LeNo: Adversarial Robust Salient Object Detection Networks with Learnable Noise


LePaRD: A Large-Scale Dataset of Judges Citing Precedents


LeRAAT: LLM-Enabled Real-Time Aviation Advisory Tool


LeRF: Learning Resampling Function for Adaptive and Efficient Image Interpolation


LeSICiN: A Heterogeneous Graph-based Approach for Automatic Legal Statute Identification from Indian Legal Documents


LeTI: Learning to Generate from Textual Interactions


LeTO: Learning Constrained Visuomotor Policy with Differentiable Trajectory Optimization


LeTac-MPC: Learning Model Predictive Control for Tactile-reactive Grasping


LeVo: High-Quality Song Generation with Multi-Preference Alignment


LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development


LeYOLO, New Scalable and Efficient CNN Architecture for Object Detection


LeaFTL: A Learning-Based Flash Translation Layer for Solid-State Drives


LeaFi: Data Series Indexes on Steroids with Learned Filters


Lead Instrument Detection from Multitrack Music


LeadCache: Regret-Optimal Caching in Networks


Leader selection in Vehicular Ad-hoc Networks: a Proactive Approach


Leader-Follower Density Control of Spatial Dynamics in Large-Scale Multi-Agent Systems


Leader-Follower Formation Tracking Control of Quadrotor UAVs Using Bearing Measurements


Leader: Prefixing a Length for Faster Word Vector Serialization


Leading Axion-Photon Sensitivity with NuSTAR Observations of M82 and M87


Leaf Counting with Deep Convolutional and Deconvolutional Networks


Leaf Only SAM: A Segment Anything Pipeline for Zero-Shot Automated Leaf Segmentation


Leaf Recognition Using Convolutional Neural Networks Based Features


Leaf: Modularity for Temporary Sharing in Separation Logic (Extended Version)


Leaf: Multiple-Choice Question Generation


LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis


LeafMask: Towards Greater Accuracy on Leaf Segmentation


LeagueAI: Improving object detector performance and flexibility through automatically generated training data and domain randomization


Leak Proof CMap; a framework for training and evaluation of cell line agnostic L1000 similarity methods


Leakage and Interpretability in Concept-Based Models


Leakage-Abuse Attacks Against Forward and Backward Private Searchable Symmetric Encryption


Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?


Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure


LeakageDetector: An Open Source Data Leakage Analysis Tool in Machine Learning Pipelines


Leaking LoRa: An Evaluation of Password Leaks and Knowledge Storage in Large Language Models


Lean Formalization of Generalization Error Bound by Rademacher Complexity


LeanBin: Harnessing Lifting and Recompilation to Debloat Binaries


LeanExplore: A search engine for Lean 4 declarations


LeanPO: Lean Preference Optimization for Likelihood Alignment in Video-LLMs


LeanReasoner: Boosting Complex Logical Reasoning with Lean


LeanStereo: A Leaner Backbone based Stereo Network


LeanVec: Searching vectors faster by making them fit


Leanabell-Prover: Posttraining Scaling in Formal Reasoning


Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval


Leaning Compact and Representative Features for Cross-Modality Person Re-Identification


Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge


Leap: Inductive Link Prediction via Learnable TopologyAugmentation


Leapfrog Diffusion Model for Stochastic Trajectory Prediction


Leapfrog Latent Consistency Model (LLCM) for Medical Images Generation


Leaping Into Memories: Space-Time Deep Feature Synthesis


Leaping Through Time with Gradient-based Adaptation for Recommendation


Leaping through tree space: continuous phylogenetic inference for rooted and unrooted trees


Learn "No" to Say "Yes" Better: Improving Vision-Language Models via Negations


Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS)


Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning


Learn Class Hierarchy using Convolutional Neural Networks


Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning


Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot


Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition


Learn From Model Beyond Fine-Tuning: A Survey


Learn From Zoom: Decoupled Supervised Contrastive Learning For WCE Image Classification


Learn Global and Optimize Local: A Data-Driven Methodology for Last-Mile Routing


Learn How to Query from Unlabeled Data Streams in Federated Learning


Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation


Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection


Learn What Is Possible, Then Choose What Is Best: Disentangling One-To-Many Relations in Language Through Text-based Games


Learn What You Need in Personalized Federated Learning


Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning


Learn Your Tokens: Word-Pooled Tokenization for Language Modeling


Learn an Effective Lip Reading Model without Pains


Learn distributed GAN with Temporary Discriminators


Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving


Learn from Foundation Model: Fruit Detection Model without Manual Annotation


Learn from Heterophily: Heterophilous Information-enhanced Graph Neural Network


Learn from Structural Scope: Improving Aspect-Level Sentiment Analysis with Hybrid Graph Convolutional Networks


Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extractionwith Rich Syntactic Knowledge


Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach


Learn from Yesterday: A Semi-Supervised Continual Learning Method for Supervision-Limited Text-to-SQL Task Streams


Learn from the Past: A Proxy Guided Adversarial Defense Framework with Self Distillation Regularization


Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detection


Learn the Force We Can: Enabling Sparse Motion Control in Multi-Object Video Generation


Learn the Time to Learn: Replay Scheduling in Continual Learning


Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control


Learn to Accumulate Evidence from All Training Samples: Theory and Practice


Learn to Combine Modalities in Multimodal Deep Learning


Learn to Differ: Sim2Real Small Defection Segmentation Network


Learn to Explain Efficiently via Neural Logic Inductive Learning


Learn to Ignore: Domain Adaptation for Multi-Site MRI Analysis


Learn to Not Link: Exploring NIL Prediction in Entity Linking


Learn to Preserve and Diversify: Parameter-Efficient Group with Orthogonal Regularization for Domain Generalization


Learn to Rapidly and Robustly Optimize Hybrid Precoding


Learn to Reason Efficiently with Adaptive Length-based Reward Shaping


Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering


Learn to Segment Retinal Lesions and Beyond


Learn to Think: Bootstrapping LLM Reasoning Capability Through Graph Learning


Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection


Learn to cycle: Time-consistent feature discovery for action recognition


Learn to synthesize and synthesize to learn


Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks


Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model


Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling


Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition


Learn2Mix: Training Neural Networks Using Adaptive Data Integration


Learn2Sing 2.0: Diffusion and Mutual Information-Based Target Speaker SVS by Learning from Singing Teacher


Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling


Learnability and Algorithm for Continual Learning


Learnability and Complexity of Quantum Samples


Learnability of Competitive Threshold Models


Learnable Activation Functions in Physics-Informed Neural Networks for Solving Partial Differential Equations


Learnable Adaptive Cosine Estimator (LACE) for Image Classification


Learnable Chamfer Distance for Point Cloud Reconstruction


Learnable Cost Volume Using the Cayley Representation


Learnable Data Augmentation for One-Shot Unsupervised Domain Adaptation


Learnable Differencing Center for Nighttime Depth Perception


Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans


Learnable Embedding Sizes for Recommender Systems


Learnable Evolutionary Multi-Objective Combinatorial Optimization via Sequence-to-Sequence Model


Learnable Graph Convolutional Attention Networks


Learnable Heterogeneous Convolution: Learning both topology and strength


Learnable Item Tokenization for Generative Recommendation


Learnable Locality-Sensitive Hashing for Video Anomaly Detection


Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection


Learnable Optimal Sequential Grouping for Video Scene Detection


Learnable Pillar-based Re-ranking for Image-Text Retrieval


Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks


Learnable Pooling Methods for Video Classification


Learnable Privacy-Preserving Anonymization for Pedestrian Images


Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain


Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation


Learnable Similarity and Dissimilarity Guided Symmetric Non-Negative Matrix Factorization


Learnable Sparse Customization in Heterogeneous Edge Computing


Learnable Spatial-Temporal Positional Encoding for Link Prediction


Learnable Spectro-temporal Receptive Fields for Robust Voice Type Discrimination


Learnable Topological Features for Phylogenetic Inference via Graph Neural Networks


Learnable Tree Filter for Structure-preserving Feature Transform


Learnable Visual Words for Interpretable Image Recognition


Learnable Weight Initialization for Volumetric Medical Image Segmentation


Learnable latent embeddings for joint behavioral and neural analysis


Learnable real-time inference of molecular composition from diffuse spectroscopy of brain tissue


Learnable wavelet neural networks for cosmological inference


Learned 1-D advection solver to accelerate air quality modeling


Learned Accelerator Framework for Angular-Distance-Based High-Dimensional DBSCAN


Learned Alternating Minimization Algorithm for Dual-domain Sparse-View CT Reconstruction


Learned Bayesian Cramér-Rao Bound for Unknown Measurement Models Using Score Neural Networks


Learned Compression of Encoding Distributions


Learned Compression of Nonlinear Time Series With Random Access


Learned Conjugate Gradient Descent Network for Massive MIMO Detection


Learned Focused Plenoptic Image Compression with Microimage Preprocessing and Global Attention


Learned Greedy Method (LGM): A Novel Neural Architecture for Sparse Coding and Beyond


Learned Gridification for Efficient Point Cloud Processing


Learned Half-Quadratic Splitting Network for MR Image Reconstruction


Learned Image Compression and Restoration for Digital Pathology


Learned Image Compression with Dictionary-based Entropy Model


Learned Inertial Odometry for Autonomous Drone Racing


Learned Lightweight Smartphone ISP with Unpaired Data


Learned Lossless Image Compression Through Interpolation With Low Complexity


Learned Monotone Minimal Perfect Hashing


Learned Perceptive Forward Dynamics Model for Safe and Platform-aware Robotic Navigation


Learned Queries for Efficient Local Attention


Learned Regularization for Inverse Problems: Insights from a Spectral Model


Learned Risk Metric Maps for Kinodynamic Systems


Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection


Learned Scalable Video Coding For Humans and Machines


Learned Scanpaths Aid Blind Panoramic Video Quality Assessment


Learned Sorted Table Search and Static Indexes in Small Model Space


Learned Thresholds Token Merging and Pruning for Vision Transformers


Learned Turbulence Modelling with Differentiable Fluid Solvers: Physics-based Loss-functions and Optimisation Horizons


Learned Video Compression with Residual Prediction and Loop Filter


Learned Weight Sharing for Deep Multi-Task Learning by Natural Evolution Strategy and Stochastic Gradient Descent


Learned codes for broadcast channels with feedback


Learned in Translation: Contextualized Word Vectors


Learned multiphysics inversion with differentiable programming and machine learning


Learned representation-guided diffusion models for large-image generation


Learned transform compression with optimized entropy encoding


LearnedFTL: A Learning-Based Page-Level FTL for Reducing Double Reads in Flash-Based SSDs


Learnergy: Energy-based Machine Learners


Learngene: From Open-World to Your Learning Task


Learning 1D Causal Visual Representation with De-focus Attention Networks


Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning


Learning 3D Garment Animation from Trajectories of A Piece of Cloth


Learning 3D Gaussians for Extremely Sparse-View Cone-Beam CT Reconstruction


Learning 3D Human Shape and Pose from Dense Body Parts


Learning 3D Mineral Prospectivity from 3D Geological Models Using Convolutional Neural Networks: Application to a Structure-controlled Hydrothermal Gold Deposit


Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations


Learning 3D Semantics from Pose-Noisy 2D Images with Hierarchical Full Attention Network


Learning 6-DoF Grasping and Pick-Place Using Attention Focus


Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration


Learning A Locally Unified 3D Point Cloud for View Synthesis


Learning A Low-Level Vision Generalist via Visual Task Prompt


Learning A Physical-aware Diffusion Model Based on Transformer for Underwater Image Enhancement


Learning A Sparse Transformer Network for Effective Image Deraining


Learning A Spiking Neural Network for Efficient Image Deraining


Learning A Unified Named Entity Tagger From Multiple Partially Annotated Corpora For Efficient Adaptation


Learning ASR-Robust Contextualized Embeddings for Spoken Language Understanding


Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking


Learning About Structural Errors in Models of Complex Dynamical Systems


Learning Abstract Visual Reasoning via Task Decomposition: A Case Study in Raven Progressive Matrices


Learning Accurate Business Process Simulation Models from Event Logs via Automated Process Discovery and Deep Learning


Learning Accurate Dense Correspondences and When to Trust Them


Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization


Learning Accurate Performance Predictors for Ultrafast Automated Model Compression


Learning Accurate Template Matching with Differentiable Coarse-to-Fine Correspondence Refinement


Learning Accurate and Enriched Features for Stereo Image Super-Resolution


Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward


Learning Acoustic Scattering Fields for Dynamic Interactive Sound Propagation


Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning


Learning Action Changes by Measuring Verb-Adverb Textual Relationships


Learning Action Conditions from Instructional Manuals for Instruction Understanding


Learning Action Embeddings for Off-Policy Evaluation


Learning Action and Reasoning-Centric Image Editing from Videos and Simulations


Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning Task


Learning Action-Transferable Policy with Action Embedding


Learning Activation Functions for Sparse Neural Networks


Learning Active Constraints to Efficiently Solve Linear Bilevel Problems: Application to the Generator Strategic Bidding Problem


Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning


Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Tracking


Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection


Learning Adaptive Parallel Reasoning with Language Models


Learning Adaptive Safety for Multi-Agent Systems


Learning Adaptive Sampling and Reconstruction for Volume Visualization


Learning Adaptive Warping for Real-World Rolling Shutter Correction


Learning Adaptive and Temporally Causal Video Tokenization in a 1D Latent Space


Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open Worlds


Learning Affine Correspondences by Integrating Geometric Constraints


Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers


Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity


Learning Agent-Aware Affordances for Closed-Loop Interaction with Articulated Objects


Learning Agile Flights through Narrow Gaps with Varying Angles using Onboard Sensing


Learning Agile Locomotion and Adaptive Behaviors via RL-augmented MPC


Learning Algebraic Multigrid Using Graph Neural Networks


Learning Algebraic Varieties from Samples


Learning Algorithms in Static Analysis of Web Applications


Learning Alternative Ways of Performing a Task


Learning Anatomically Consistent Embedding for Chest Radiography


Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstruction


Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population


Learning Apparent Diffusion Coefficient Maps from Accelerated Radial k-Space Diffusion-Weighted MRI in Mice using a Deep CNN-Transformer Model


Learning Approximate Forward Reachable Sets Using Separating Kernels


Learning Approximate Stochastic Transition Models


Learning Arousal-Valence Representation from Categorical Emotion Labels of Speech


Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network


Learning Associative Inference Using Fast Weight Memory


Learning Asymmetric and Local Features in Multi-Dimensional Data through Wavelets with Recursive Partitioning


Learning Atomic Multipoles: Prediction of the Electrostatic Potential with Equivariant Graph Neural Networks


Learning Attention as Disentangler for Compositional Zero-shot Learning


Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs


Learning Attraction Field Representation for Robust Line Segment Detection


Learning Attractor Dynamics for Generative Memory


Learning Attributed Graph Representations with Communicative Message Passing Transformer


Learning Audio Concepts from Counterfactual Natural Language


Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting


Learning Audio-Visual Source Localization via False Negative Aware Contrastive Learning


Learning Augmented Energy Minimization via Speed Scaling


Learning Autocomplete Systems as a Communication Game


Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks


Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations


Learning Barrier-Certified Polynomial Dynamical Systems for Obstacle Avoidance with Robots


Learning Based Dynamic Cluster Reconfiguration for UAV Mobility Management with 3D Beamforming


Learning Bayesian Networks from Ordinal Data


Learning Beam Codebooks with Neural Networks: Towards Environment-Aware mmWave MIMO


Learning Behaviors with Uncertain Human Feedback


Learning Belief Representations for Imitation Learning in POMDPs


Learning Bellman Complete Representations for Offline Policy Evaluation


Learning Best Combination for Efficient N:M Sparsity


Learning Better Keypoints for Multi-Object 6DoF Pose Estimation


Learning Better Lossless Compression Using Lossy Compression


Learning Better Masking for Better Language Model Pre-training


Learning Better Representations From Less Data For Propositional Satisfiability


Learning Better Visual Dialog Agents with Pretrained Visual-Linguistic Representation


Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing


Learning Beyond the Surface: How Far Can Continual Pre-Training with LoRA Enhance LLMs' Domain-Specific Insight Learning?


Learning Bi-typed Multi-relational Heterogeneous Graph via Dual Hierarchical Attention Networks


Learning Bifunctional Push-grasping Synergistic Strategy for Goal-agnostic and Goal-oriented Tasks


Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories


Learning Bill Similarity with Annotated and Augmented Corpora of Bills


Learning Binary Color Filter Arrays with Trainable Hard Thresholding


Learning Binary Decision Trees by Argmin Differentiation


Learning Binary Latent Variable Models: A Tensor Eigenpair Approach


Learning Blind Video Temporal Consistency


Learning Bloch Simulations for MR Fingerprinting by Invertible Neural Networks


Learning Bodily and Temporal Attention in Protective Movement Behavior Detection


Learning Bottleneck Concepts in Image Classification


Learning Bounded Context-Free-Grammar via LSTM and the Transformer:Difference and Explanations


Learning Bounds for Risk-sensitive Learning


Learning Brain Tumor Representation in 3D High-Resolution MR Images via Interpretable State Space Models


Learning Broken Symmetries with Approximate Invariance


Learning Broken Symmetries with Resimulation and Encouraged Invariance


Learning C to x86 Translation: An Experiment in Neural Compilation


Learning CHARME models with neural networks


Learning COVID-19 Regional Transmission Using Universal Differential Equations in a SIR model


Learning Calibrated-Guidance for Object Detection in Aerial Images


Learning Camera Localization via Dense Scene Matching


Learning Camera Miscalibration Detection


Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views