Total Variation Regularization for Compartmental Epidemic Models with Time-Varying Dynamics


Total energy-shaping control for mechanical systems via Control-by-Interconnection


Total fraction of drug released from diffusion-controlled delivery systems with binding reactions


Total variation regularization with variable Lebesgue prior


Total-Decom: Decomposed 3D Scene Reconstruction with Minimal Interaction


Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis


Total-Variation -- Fast Gradient Flow and Relations to Koopman Theory


Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image


Totally deranged elements of almost simple groups and invariable generating sets


Totally symmetric sets in the general linear group


Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation


Touch-based Curiosity for Sparse-Reward Tasks


TouchStone: Evaluating Vision-Language Models by Language Models


Touched by ChatGPT: Using an LLM to Drive Affective Tactile Interaction


Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?


Tougher Text, Smarter Models: Raising the Bar for Adversarial Defence Benchmarks


ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning


TourLLM: Enhancing LLMs with Tourism Knowledge


TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy


TourSynbio: A Multi-Modal Large Model and Agent Framework to Bridge Text and Protein Sequences for Protein Engineering


Tourneys and the Fast Generation and Obfuscation of Closed Knight's Tours


Toward 3D Object Reconstruction from Stereo Images


Toward A Formalized Approach for Spike Sorting Algorithms and Hardware Evaluation


Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating and Programming Biology at All Levels


Toward Accurate and Temporally Consistent Video Restoration from Raw Data


Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and Benchmark


Toward Adversarial Robustness via Semi-supervised Robust Training


Toward Adversarial Training on Contextualized Language Representation


Toward Aligning Human and Robot Actions via Multi-Modal Demonstration Learning


Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early Classification


Toward Attention-based TinyML: A Heterogeneous Accelerated Architecture and Automated Deployment Flow


Toward Automated Early Sepsis Alerting: Identifying Infection Patients from Nursing Notes


Toward Automated Simulation Research Workflow through LLM Prompt Engineering Design


Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks


Toward Causal-Aware RL: State-Wise Action-Refined Temporal Difference


Toward Clinically Assisted Colorectal Polyp Recognition via Structured Cross-modal Representation Consistency


Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language


Toward Conditional Distribution Calibration in Survival Prediction


Toward Connecting Speech Acts and Search Actions in Conversational Search Tasks


Toward Consistent and Efficient Map-based Visual-inertial Localization: Theory Framework and Filter Design


Toward Controlling Discrimination in Online Ad Auctions


Toward Conversational Agents with Context and Time Sensitive Long-term Memory


Toward Cost-effective Adaptive Random Testing: An Approximate Nearest Neighbor Approach


Toward DNN of LUTs: Learning Efficient Image Restoration with Multiple Look-Up Tables


Toward Degree Bias in Embedding-Based Knowledge Graph Completion


Toward Dialogue Modeling: A Semantic Annotation Scheme for Questions and Answers


Toward Dynamic Stability Assessment of Power Grid Topologies using Graph Neural Networks


Toward Efficient Convolutional Neural Networks With Structured Ternary Patterns


Toward Efficient and Incremental Spectral Clustering via Parametric Spectral Clustering


Toward Efficient and Robust Multiple Camera Visual-inertial Odometry


Toward End-to-End, Full-Stack 6G Terahertz Networks


Toward Enhancing Vehicle Color Recognition in Adverse Conditions: A Dataset and Benchmark


Toward Evaluating Robustness of Reinforcement Learning with Adversarial Policy


Toward Evaluative Thinking: Meta Policy Optimization with Evolving Reward Models


Toward Explainable AI for Regression Models


Toward Explainable NILM: Real-Time Event-Based NILM Framework for High-Frequency Data


Toward Extremely Lightweight Distracted Driver Recognition With Distillation-Based Neural Architecture Search and Knowledge Transfer


Toward Extremely Precise Radial Velocities: II. A Tool For Using Multivariate Gaussian Processes to Model Stellar Activity


Toward Fair Federated Learning under Demographic Disparities and Data Imbalance


Toward Falsifying Causal Graphs Using a Permutation-Based Test


Toward Fast and Provably Accurate Near-field Ptychographic Phase Retrieval


Toward Fast, Flexible, and Robust Low-Light Image Enhancement


Toward Finding Strong Pareto Optimal Policies in Multi-Agent Reinforcement Learning


Toward Fine-grained Facial Expression Manipulation


Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework


Toward Fully Self-Supervised Multi-Pitch Estimation


Toward Fully-End-to-End Listened Speech Decoding from EEG Signals


Toward Gender-Inclusive Coreference Resolution


Toward General Instruction-Following Alignment for Retrieval-Augmented Generation


Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Estimating Sample Size and Reducing Overfitting


Toward Generation of Test Cases from Task Descriptions via History-aware Planning


Toward Global Sensing Quality Maximization: A Configuration Optimization Scheme for Camera Networks


Toward Globally Optimal State Estimation Using Automatically Tightened Semidefinite Relaxations


Toward Greener Matrix Operations by Lossless Compressed Formats


Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications


Toward Human-Quantum Computer Interaction: Interface Techniques for Usable Quantum Computing


Toward Improving Coherence and Diversity of Slogan Generation


Toward Improving Robustness of Object Detectors Against Domain Shift


Toward Informal Language Processing: Knowledge of Slang in Large Language Models


Toward Informed AV Decision-Making: Computational Model of Well-being and Trust in Mobility


Toward Integrated Sensing and Communications in IEEE 802.11bf Wi-Fi Networks


Toward Intelligent and Secure Cloud: Large Language Model Empowered Proactive Defense


Toward Interpretable Semantic Textual Similarity via Optimal Transport-based Contrastive Sentence Learning


Toward Interpretable Sleep Stage Classification Using Cross-Modal Transformers


Toward Knowledge-Driven Speech-Based Models of Depression: Leveraging Spectrotemporal Variations in Speech Vowels


Toward Lightweight and Fast Decoders for Diffusion Models in Image and Video Generation


Toward Long-Term and Archivable Reproducibility


Toward Low-latency Iterative Decoding of QLDPC Codes Under Circuit-Level Noise


Toward Memory-Aided World Models: Benchmarking via Spatial Consistency


Toward Micro-Dialect Identification in Diaglossic and Code-Switched Environments


Toward Minimal Misalignment at Minimal Cost in One-Stage and Anchor-Free Object Detection


Toward More Reliable Analytic Thermochemical-equilibrium Abundances


Toward Multi-Session Personalized Conversation: A Large-Scale Dataset and Hierarchical Tree Framework for Implicit Reasoning


Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond


Toward Neural-Network-Guided Program Synthesis and Verification


Toward Optimal LLM Alignments Using Two-Player Games


Toward Optimal Probabilistic Active Learning Using a Bayesian Approach


Toward Optimal Tabletop Rearrangement with Multiple Manipulation Primitives


Toward Optimized VR/AR Ergonomics: Modeling and Predicting User Neck Muscle Contraction


Toward Physics-Aware Deep Learning Architectures for LiDAR Intensity Simulation


Toward Practical Monocular Indoor Depth Estimation


Toward Programming Languages for Reasoning: Humans, Symbolic Systems, and AI Agents


Toward Real Text Manipulation Detection: New Dataset and New Solution


Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information


Toward Real-Time Digital Twins of EM Environments: Computational Benchmark of Ray Launching Software


Toward Real-Time Edge AI: Model-Agnostic Task-Oriented Communication with Visual Feature Alignment


Toward Real-Time Image Annotation Using Marginalized Coupled Dictionary Learning


Toward Real-World Light Field Super-Resolution


Toward Real-world Single Image Deraining: A New Benchmark and Beyond


Toward Realistic Camouflaged Object Detection: Benchmarks and Method


Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts


Toward Reliable Ad-hoc Scientific Information Extraction: A Case Study on Two Materials Datasets


Toward Reliable Biomedical Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models


Toward Reliable Human Pose Forecasting with Uncertainty


Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection


Toward Robust Early Detection of Alzheimer's Disease via an Integrated Multimodal Learning Approach


Toward Robust Manufacturing Scheduling: Stochastic Job-Shop Scheduling


Toward Robust Non-Transferable Learning: A Survey and Benchmark


Toward Robust RALMs: Revealing the Impact of Imperfect Retrieval on Retrieval-Augmented Language Models


Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise


Toward Safe and Accelerated Deep Reinforcement Learning for Next-Generation Wireless Networks


Toward Scalable Neural Dialogue State Tracking Model


Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing


Toward Spatial Temporal Consistency of Joint Visual Tactile Perception in VR Applications


Toward Stronger Textual Attack Detectors


Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach


Toward Sufficient Spatial-Frequency Interaction for Gradient-aware Underwater Image Enhancement


Toward Sustainable Polymer Design: A Molecular Dynamics-Informed Machine Learning Approach for Vitrimers


Toward Tag-free Aspect Based Sentiment Analysis: A Multiple Attention Network Approach


Toward Training at ImageNet Scale with Differential Privacy


Toward Understanding Deep Learning Framework Bugs


Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition


Toward Understanding the Disagreement Problem in Neural Network Feature Attribution


Toward Unified Controllable Text Generation via Regular Expression Instruction


Toward Unifying Text Segmentation and Long Document Summarization


Toward Universal Decoding of Binary Linear Block Codes via Enhanced Polar Transformations


Toward Unsupervised 3D Point Cloud Anomaly Detection using Variational Autoencoder


Toward Unsupervised Outlier Model Selection


Toward Value-oriented Renewable Energy Forecasting: An Iterative Learning Approach


Toward Verifiable Real-Time Obstacle Motion Prediction for Dynamic Collision Avoidance


Toward Zero-Shot Learning for Visual Dehazing of Urological Surgical Robots


Toward Zero-Shot Sim-to-Real Transfer Learning for Pneumatic Soft Robot 3D Proprioceptive Sensing


Toward Zero-Shot Unsupervised Image-to-Image Translation


Toward a 2D Local Implementation of Quantum LDPC Codes


Toward a Better Understanding of Cosmic Chronometers: Stellar Population Properties of Passive Galaxies at Intermediate Redshift


Toward a Better Understanding of Loss Functions for Collaborative Filtering


Toward a Generalization Metric for Deep Generative Models


Toward a Knowledge Discovery Framework for Data Science Job Market in the United States


Toward a Mapping of Capability and Skill Models using Asset Administration Shells and Ontologies


Toward a Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (a Case Study and Framework for Progress)


Toward a Procedural Fruit Tree Rendering Framework for Image Analysis


Toward a Secure Crowdsourced Location Tracking System


Toward a Standardized and More Accurate Indonesian Part-of-Speech Tagging


Toward a Surgeon-in-the-Loop Ophthalmic Robotic Apprentice using Reinforcement and Imitation Learning


Toward a Visual Concept Vocabulary for GAN Latent Space


Toward a Wearable Biosensor Ecosystem on ROS 2 for Real-time Human-Robot Interaction Systems


Toward a certified greedy Loewner framework with minimal sampling


Toward an AI Physicist for Unsupervised Learning


Toward an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets


Toward an Idiomatic Framework for Cognitive Robotics


Toward an Integrated Decision Making Framework for Optimized Stroke Diagnosis with DSA and Treatment under Uncertainty


Toward asynchronous EEG-based BCI: Detecting imagined words segments in continuous EEG signals


Toward automated detection of light echoes in synoptic surveys: considerations on the application of the Deep Convolutional Neural Networks


Toward effective protection against diffusion based mimicry through score distillation


Toward interoperable representation and sharing of disinformation incidents in cyber threat intelligence


Toward matter dynamics in spin foam quantum gravity


Toward multi-target self-organizing pursuit in a partially observable Markov game


Toward optimal-scaling DFT: stochastic Hartree theory in the thermodynamic and complete basis set limits at arbitrary temperature


Toward quantitative fractography using convolutional neural networks


Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX


Toward robust detections of nanohertz gravitational waves


Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper


Toward the unambiguous identification of supermassive binary black holes through Bayesian inference


Toward unsupervised, multi-object discovery in large-scale image collections


Towards "simultaneous selective inference": post-hoc bounds on the false discovery proportion


Towards 3D Face Reconstruction in Perspective Projection: Estimating 6DoF Face Pose from Monocular Image


Towards 3D Molecule-Text Interpretation in Language Models


Towards 3D-Printed Inverse-Designed Metaoptics


Towards 6D MCL for LiDARs in 3D TSDF Maps on Embedded Systems with GPUs


Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning


Towards A Human-in-the-Loop LLM Approach to Collaborative Discourse Analysis


Towards A Proactive ML Approach for Detecting Backdoor Poison Samples


Towards A Unified Conformer Structure: from ASR to ASV Task


Towards A Unified View of Answer Calibration for Multi-Step Reasoning


Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling


Towards AI-Assisted Synthesis of Verified Dafny Methods


Towards AI-assisted Neutrino Flavor Theory Design


Towards Abstractive Grounded Summarization of Podcast Transcripts


Towards Abstractive Timeline Summarisation using Preference-based Reinforcement Learning


Towards Accurate Active Camera Localization


Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies


Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism


Towards Accurate Cross-Domain In-Bed Human Pose Estimation


Towards Accurate Ground Plane Normal Estimation from Ego-Motion


Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization


Towards Accurate Post-training Quantization for Diffusion Models


Towards Accurate Post-training Quantization for Reparameterized Models


Towards Accurate Prediction of Configurational Disorder Properties in Materials using Graph Neural Networks


Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning


Towards Accurate Text-based Image Captioning with Content Diversity Exploration


Towards Accurate Translation via Semantically Appropriate Application of Lexical Constraints


Towards Accurate Unified Anomaly Segmentation


Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction


Towards Accurate and Interpretable Neuroblastoma Diagnosis via Contrastive Multi-scale Pathological Image Analysis


Towards Accurate and Reliable Energy Measurement of NLP Models


Towards Accurate and Robust Domain Adaptation under Noisy Environments


Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes


Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent


Towards Action Model Learning for Player Modeling


Towards Actionable Pedagogical Feedback: A Multi-Perspective Analysis of Mathematics Teaching and Tutoring Dialogue


Towards Activated Muscle Group Estimation in the Wild


Towards Adapting Open-Source Large Language Models for Expert-Level Clinical Note Generation


Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking


Towards Adaptive Storage Views in Virtual Memory


Towards Adaptive Subspace Detection in Heterogeneous Environment


Towards Adversarial Attack on Vision-Language Pre-training Models


Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting


Towards Adversarial Retinal Image Synthesis


Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentation


Towards Adversarially Robust Dataset Distillation by Curvature Regularization


Towards Algebraic Subtyping for Extensible Records


Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values


Towards Algorithmic Fidelity: Mental Health Representation across Demographics in Synthetic vs. Human-generated Data


Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints


Towards All-in-One Medical Image Re-Identification


Towards Alleviating the Object Bias in Prompt Tuning-based Factual Knowledge Extraction


Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations


Towards Alzheimer's Disease Classification through Transfer Learning


Towards Ambiguity-Free Spatial Foundation Model: Rethinking and Decoupling Depth Ambiguity


Towards An Efficient and Effective En Route Travel Time Estimation Framework


Towards An Unsupervised Learning Scheme for Efficiently Solving Parameterized Mixed-Integer Programs


Towards Analytical Electromagnetic Models for Reconfigurable Intelligent Surfaces


Towards Answering Climate Questionnaires from Unstructured Climate Reports


Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt


Towards Anytime Optical Flow Estimation with Event Cameras


Towards Arabic Multimodal Dataset for Sentiment Analysis


Towards Architecting Sustainable MLOps: A Self-Adaptation Approach


Towards Architecture-Agnostic Untrained Network Priors for Image Reconstruction with Frequency Regularization


Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Reranking


Towards Artificial Intelligence Research Assistant for Expert-Involved Learning


Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method


Towards Assessing Compliant Robotic Grasping from First-Object Perspective via Instrumented Objects


Towards Assessing Data Replication in Music Generation with Music Similarity Metrics on Raw Audio


Towards Asteroid Detection in Microlensing Surveys with Deep Learning


Towards Attack-tolerant Federated Learning via Critical Parameter Analysis


Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation


Towards Auction-Based Function Placement in Serverless Fog Platforms


Towards Audio Codec-based Speech Separation


Towards Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning


Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflows


Towards Autoencoding Variational Inference for Aspect-based Opinion Summary


Towards Autoformalization of Mathematics and Code Correctness: Experiments with Elementary Proofs


Towards Automated Application-Specific Software Stacks


Towards Automated Augmentation and Instrumentation of Legacy Cryptographic Executables: Extended Version


Towards Automated Benchmarking of Atomistic Forcefields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive


Towards Automated Circuit Discovery for Mechanistic Interpretability


Towards Automated Classification of Code Review Feedback to Support Analytics


Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis


Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond


Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements


Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection


Towards Automatic Bias Detection in Knowledge Graphs


Towards Automatic Comparison of Data Privacy Documents: A Preliminary Experiment on GDPR-like Laws


Towards Automatic Face-to-Face Translation


Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack Music


Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code


Towards Automatic Speech to Sign Language Generation


Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?


Towards Automatically Extracting UML Class Diagrams from Natural Language Specifications


Towards Automatically Generating Release Notes using Extractive Summarization Technique


Towards Automating Code Review Activities


Towards Automating the Retrospective Generation of BIM Models: A Unified Framework for 3D Semantic Reconstruction of the Built Environment


Towards Autonomous 1/8th Offroad RC Racing -- The TruggySense Educational Platform


Towards Autonomous Atlas-based Ultrasound Acquisitions in Presence of Articulated Motion


Towards Autonomous Crop-Agnostic Visual Navigation in Arable Fields


Towards Autonomous Cybersecurity: An Intelligent AutoML Framework for Autonomous Intrusion Detection


Towards Backdoor Stealthiness in Model Parameter Space


Towards Backward-Compatible Continual Learning of Image Compression


Towards Backward-Compatible Representation Learning


Towards Backwards-Compatible Data with Confounded Domain Adaptation


Towards Balanced Active Learning for Multimodal Classification


Towards Balanced Alignment: Modal-Enhanced Semantic Modeling for Video Moment Retrieval


Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfer


Towards Being Parameter-Efficient: A Stratified Sparsely Activated Transformer with Dynamic Capacity


Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks


Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models


Towards Best Experiment Design for Evaluating Dialogue System Output


Towards Best Practice of Interpreting Deep Learning Models for EEG-based Brain Computer Interfaces


Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards


Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion


Towards Better Bounds for Finding Quasi-Identifiers


Towards Better Certified Segmentation via Diffusion Models


Towards Better Chinese-centric Neural Machine Translation for Low-resource Languages


Towards Better Data Exploitation in Self-Supervised Monocular Depth Estimation


Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification


Towards Better Document-level Relation Extraction via Iterative Inference


Towards Better Domain Adaptation for Self-supervised Models: A Case Study of Child ASR


Towards Better Entity Linking with Multi-View Enhanced Distillation


Towards Better Evaluation for Dynamic Link Prediction


Towards Better Evaluation for Generated Patent Claims


Towards Better Explanations for Object Detection


Towards Better Forecasting by Fusing Near and Distant Future Visions


Towards Better Graph-based Cross-document Relation Extraction via Non-bridge Entity Enhancement and Prediction Debiasing


Towards Better Inclusivity: A Diverse Tweet Corpus of English Varieties


Towards Better Multi-head Attention via Channel-wise Sample Permutation


Towards Better Multi-modal Keyphrase Generation via Visual Entity Enhancement and Multi-granularity Image Noise Filtering


Towards Better Object Detection in Scale Variation with Adaptive Feature Selection


Towards Better Open-Ended Text Generation: A Multicriteria Evaluation Framework


Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks


Towards Better Semantic Understanding of Mobile Interfaces


Towards Better Statistical Understanding of Watermarking LLMs


Towards Better Test Coverage: Merging Unit Tests for Autonomous Systems


Towards Better Understanding of Contrastive Sentence Representation Learning: A Unified Paradigm for Gradient


Towards Better Understanding of User Satisfaction in Open-Domain Conversational Search


Towards Better Visualizing the Decision Basis of Networks via Unfold and Conquer Attribution Guidance


Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions


Towards Binary-Valued Gates for Robust LSTM Training


Towards Biologically Plausible Convolutional Networks


Towards Biologically Plausible and Private Gene Expression Data Generation


Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms


Towards Boosting Many-to-Many Multilingual Machine Translation with Large Language Models


Towards Boosting the Accuracy of Non-Latin Scene Text Recognition


Towards Both Accurate and Robust Neural Networks without Extra Data


Towards Bridging the Cross-modal Semantic Gap for Multi-modal Recommendation


Towards Bridging the Performance Gaps of Joint Energy-based Models


Towards Building A Group-based Unsupervised Representation Disentanglement Framework


Towards Building Knowledge by Merging Multiple Ontologies with CoMerger: A Partitioning-based Approach


Towards Building Multilingual Language Model for Medicine


Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects


Towards Building a Knowledge Base of Monetary Transactions from a News Collection


Towards Building an End-to-End Multilingual Automatic Lyrics Transcription Model


Towards Building the Federated GPT: Federated Instruction Tuning


Towards CPU Performance Prediction: New Challenge Benchmark Dataset and Novel Approach


Towards Calibrated Deep Clustering Network


Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-tailed Learning


Towards Calibrated Losses for Adversarial Robust Reject Option Classification


Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective


Towards Calibrated Robust Fine-Tuning of Vision-Language Models


Towards Carbon Footprint-Aware Recommender Systems for Greener Item Recommendation


Towards Cardiac MRI Foundation Models: Comprehensive Visual-Tabular Representations for Whole-Heart Assessment and Beyond


Towards Causal Inference for Spatio-Temporal Data: Conflict and Forest Loss in Colombia


Towards Causal Relationship in Indefinite Data: Baseline Model and New Datasets


Towards Causality-Aware Inferring: A Sequential Discriminative Approach for Medical Diagnosis


Towards Certified Robustness of Distance Metric Learning


Towards Certified Unlearning for Deep Neural Networks


Towards Characterization of 5-List-Colorability of Toroidal Graphs


Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models


Towards Characterizing International Routing Detours


Towards Cleaning-up Open Data Portals: A Metadata Reconciliation Approach


Towards Climate Awareness in NLP Research


Towards Clinical Prediction with Transparency: An Explainable AI Approach to Survival Modelling in Residential Aged Care


Towards Closing the Sim-to-Real Gap in Collaborative Multi-Robot Deep Reinforcement Learning


Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering


Towards Coarse-to-Fine Evaluation of Inference Efficiency for Large Language Models


Towards Codable Watermarking for Injecting Multi-bits Information to LLMs


Towards Code Watermarking with Dual-Channel Transformations


Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models


Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering


Towards Collaborative Anti-Money Laundering Among Financial Institutions


Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System


Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs


Towards Collaborative Plan Acquisition through Theory of Mind Modeling in Situated Dialogue


Towards Commonsense Knowledge based Fuzzy Systems for Supporting Size-Related Fine-Grained Object Detection


Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation


Towards Community-Driven Agents for Machine Learning Engineering


Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning


Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination


Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation


Towards Complete Causal Explanation with Expert Knowledge


Towards Completeness-Oriented Tool Retrieval for Large Language Models


Towards Completeness: A Generalizable Action Proposal Generator for Zero-Shot Temporal Action Localization


Towards Complex Backgrounds: A Unified Difference-Aware Decoder for Binary Segmentation


Towards Compositionality in Concept Learning


Towards Comprehensive Detection of Chinese Harmful Memes


Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks


Towards Computational Linguistics in Minangkabau Language: Studies on Sentiment Analysis and Machine Translation


Towards Computational Performance Engineering for Unsupervised Concept Drift Detection -- Complexities, Benchmarking, Performance Analysis


Towards Computationally Efficient Responsibility Attribution in Decentralized Partially Observable MDPs


Towards Computationally Feasible Deep Active Learning


Towards Computing an Optimal Abstraction for Structural Causal Models


Towards Concept-Aware Large Language Models


Towards Concept-based Interpretability of Skin Lesion Diagnosis using Vision-Language Models


Towards Conceptualization of "Fair Explanation": Disparate Impacts of anti-Asian Hate Speech Explanations on Content Moderators


Towards Conditional Generation of Minimal Action Potential Pathways for Molecular Dynamics


Towards Confidence-guided Shape Completion for Robotic Applications


Towards Consensus: Reducing Polarization by Perturbing Social Networks


Towards Consistency and Complementarity: A Multiview Graph Information Bottleneck Approach


Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning


Towards Constituting Mathematical Structures for Learning to Optimize


Towards Constraint-aware Learning for Resource Allocation in NFV-enabled Networks


Towards Content-based Pixel Retrieval in Revisited Oxford and Paris


Towards Context-Agnostic Learning Using Synthetic Data


Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems


Towards Continual Egocentric Activity Recognition: A Multi-modal Egocentric Activity Dataset for Continual Learning


Towards Continual Knowledge Graph Embedding via Incremental Distillation


Towards Controllable Biases in Language Generation


Towards Controllable Speech Synthesis in the Era of Large Language Models: A Survey


Towards Counterfactual Image Manipulation via CLIP


Towards Coupling Full-disk and Active Region-based Flare Prediction for Operational Space Weather Forecasting


Towards Cover Song Detection with Siamese Convolutional Neural Networks


Towards Croppable Implicit Neural Representations


Towards Cross-Disaster Building Damage Assessment with Graph Convolutional Networks


Towards Cross-Domain Single Blood Cell Image Classification via Large-Scale LoRA-based Segment Anything Model


Towards Cross-Lingual Audio Abuse Detection in Low-Resource Settings with Few-Shot Learning


Towards Cross-Modal Text-Molecule Retrieval with Better Modality Alignment


Towards Cross-Provider Analysis of Transparency Information for Data Protection


Towards Cross-Scale Attention and Surface Supervision for Fractured Bone Segmentation in CT


Towards Cross-Table Masked Pretraining for Web Data Mining


Towards Cross-View-Consistent Self-Supervised Surround Depth Estimation


Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts


Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations


Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges


Towards Data Valuation via Asymmetric Data Shapley


Towards Data-Conditional Simulation for ABC Inference in Stochastic Differential Equations


Towards Data-Driven Offline Simulations for Online Reinforcement Learning


Towards Data-Efficient Pretraining for Atomic Property Prediction


Towards Data-centric Graph Machine Learning: Review and Outlook


Towards Dataset Copyright Evasion Attack against Personalized Text-to-Image Diffusion Models


Towards Debiasing Sentence Representations


Towards Debugging Deep Neural Networks by Generating Speech Utterances


Towards Decentralized Task Offloading and Resource Allocation in User-Centric Mobile Edge Computing


Towards Decoding Brain Activity During Passive Listening of Speech


Towards Deep Cellular Phenotyping in Placental Histology


Towards Deep Learning Models Resistant to Large Perturbations


Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans


Towards Deep and Efficient: A Deep Siamese Self-Attention Fully Efficient Convolutional Network for Change Detection in VHR Images


Towards Deeper Graph Neural Networks with Differentiable Group Normalization


Towards Deeper Understanding of PPR-based Embedding Approaches: A Topological Perspective


Towards Deeply Unified Depth-aware Panoptic Segmentation with Bi-directional Guidance Learning


Towards Defending Multiple $\ell_p$-norm Bounded Adversarial Perturbations via Gated Batch Normalization


Towards Democratizing AI: A Comparative Analysis of AI as a Service Platforms and the Open Space for Machine Learning Approach


Towards Democratizing Joint-Embedding Self-Supervised Learning


Towards Demystifying Dimensions of Source Code Embeddings


Towards Demystifying Serverless Machine Learning Training


Towards Dense and Accurate Radar Perception Via Efficient Cross-Modal Diffusion Model


Towards Designing and Exploiting Generative Networks for Neutrino Physics Experiments using Liquid Argon Time Projection Chambers


Towards Detecting Contextual Real-Time Toxicity for In-Game Chat


Towards Detecting Harmful Agendas in News Articles


Towards Detecting Inauthentic Coordination in Twitter Likes Data


Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution


Towards Detection of Subjective Bias using Contextualized Word Embeddings


Towards Development with Multi-Version Models: Detecting Merge Conflicts and Checking Well-Formedness


Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm


Towards Discovery and Attribution of Open-world GAN Generated Images


Towards Disentangling Information Paths with Coded ResNeXt


Towards Disentangling Latent Space for Unsupervised Semantic Face Editing


Towards Distortion-Predictable Embedding of Neural Networks


Towards Distribution Matching between Collaborative and Language Spaces for Generative Recommendation


Towards Disturbance-Free Visual Mobile Manipulation


Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration


Towards Diverse Paragraph Captioning for Untrimmed Videos


Towards Diverse Temporal Grounding under Single Positive Labels


Towards Diverse and Effective Question-Answer Pair Generation from Children Storybooks


Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks


Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reordering


Towards Domain Generalization for ECG and EEG Classification: Algorithms and Benchmarks


Towards Domain-agnostic Depth Completion


Towards Driving-Oriented Metric for Lane Detection Models


Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case


Towards Dynamic Causal Discovery with Rare Events: A Nonparametric Conditional Independence Test


Towards Dynamic Message Passing on Graphs


Towards Dynamic Theory of Mind: Evaluating LLM Adaptation to Temporal Evolution of Human States


Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning


Towards Earlier Detection of Oral Diseases On Smartphones Using Oral and Dental RGB Images


Towards Early Prediction of Human iPSC Reprogramming Success


Towards Economical Inference: Enabling DeepSeek's Multi-Head Latent Attention in Any Transformer-based LLMs


Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation


Towards Effective Authorship Attribution: Integrating Class-Incremental Learning


Towards Effective Code-Integrated Reasoning


Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning


Towards Effective Counter-Responses: Aligning Human Preferences with Strategies to Combat Online Trolling


Towards Effective Detection of Ponzi schemes on Ethereum with Contract Runtime Behavior Graph


Towards Effective Discrimination Testing for Generative AI


Towards Effective GenAI Multi-Agent Collaboration: Design and Evaluation for Enterprise Applications


Towards Effective Image Manipulation Detection with Proposal Contrastive Learning


Towards Effective Issue Assignment using Online Machine Learning


Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy


Towards Effective Paraphrasing for Information Disguise


Towards Effective Visual Representations for Partial-Label Learning


Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking


Towards Effective and Efficient Context-aware Nucleus Detection in Histopathology Whole Slide Images


Towards Effective and General Graph Unlearning via Mutual Evolution


Towards Effective and Sparse Adversarial Attack on Spiking Neural Networks via Breaking Invisible Surrogate Gradients


Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space


Towards Efficient 3D Object Detection with Knowledge Distillation


Towards Efficient Benchmarking of Foundation Models in Remote Sensing: A Capabilities Encoding Approach


Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training


Towards Efficient Diffusion-Based Image Editing with Instant Attention Masks


Towards Efficient Exact Optimization of Language Model Alignment


Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond


Towards Efficient Local Causal Structure Learning


Towards Efficient MPPI Trajectory Generation with Unscented Guidance: U-MPPI Control Strategy


Towards Efficient Methods in Medical Question Answering using Knowledge Graph Embeddings


Towards Efficient NLP: A Standard Evaluation and A Strong Baseline


Towards Efficient Pareto Set Approximation via Mixture of Experts Based Model Fusion


Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering


Towards Efficient SDRTV-to-HDRTV by Learning from Image Formation


Towards Efficient Subarray Hybrid Beamforming: Attention Network-based Practical Feedback in FDD Massive MU-MIMO Systems


Towards Efficient Target-Level Machine Unlearning Based on Essential Graph


Towards Efficient Trajectory Generation for Ground Robots beyond 2D Environment


Towards Efficient Verification of Quantized Neural Networks


Towards Efficient Visual Adaption via Structural Re-parameterization


Towards Efficient Visual-Language Alignment of the Q-Former for Visual Reasoning Tasks


Towards Efficient and Effective Deep Clustering with Dynamic Grouping and Prototype Aggregation


Towards Efficient and Effective Self-Supervised Learning of Visual Representations


Towards Efficient and Effective Text-to-Video Retrieval with Coarse-to-Fine Visual Representation Learning


Towards Efficient and Effective Unlearning of Large Language Models for Recommendation


Towards Efficient and Explainable Hate Speech Detection via Model Distillation


Towards Efficient and Multifaceted Computer-assisted Pronunciation Training Leveraging Hierarchical Selective State Space Model and Decoupled Cross-entropy Loss


Towards Efficient and Robust VQA-NLE Data Generation with Large Vision-Language Models


Towards Efficient and Scalable Training of Differentially Private Deep Learning


Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing


Towards Efficiently Diversifying Dialogue Generation via Embedding Augmentation


Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks


Towards Emergency Scenarios: An Integrated Decision-making Framework of Multi-lane Platoon Reorganization


Towards Emotion Analysis in Short-form Videos: A Large-Scale Dataset and Baseline


Towards Emotion Recognition in Hindi-English Code-Mixed Data: A Transformer Based Approach


Towards Emotional Support Dialog Systems


Towards Empathetic Conversational Recommender Systems


Towards Empirical Interpretation of Internal Circuits and Properties in Grokked Transformers on Modular Polynomials


Towards Enabling Meta-Learning from Target Models


Towards End-User Development for IoT: A Case Study on Semantic Parsing of Cooking Recipes for Programming Kitchen Devices


Towards End-to-End GPS Localization with Neural Pseudorange Correction


Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers


Towards End-to-End Image Compression and Analysis with Transformers


Towards End-to-End Learning for Dialog State Tracking and Management using Deep Reinforcement Learning


Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access


Towards End-to-End Structure Solutions from Information-Compromised Diffraction Data via Generative Deep Learning


Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgin


Towards End-to-end Semi-supervised Learning for One-stage Object Detection


Towards End-to-end Speech-to-text Summarization


Towards End-to-end Video-based Eye-Tracking


Towards Energy- and QoS-aware Load Balancing for 6G: Leveraging O-RAN to Achieve Sustainable and Energy-Efficient 6G


Towards Energy-Aware Federated Learning on Battery-Powered Clients


Towards Engineering Fair and Equitable Software Systems for Managing Low-Altitude Airspace Authorizations


Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency


Towards Enhanced Immersion and Agency for LLM-based Interactive Drama


Towards Enhanced RAC Accessibility: Leveraging Datasets and LLMs


Towards Enhancing Coherence in Extractive Summarization: Dataset and Experiments with LLMs


Towards Enhancing Fault Tolerance in Neural Networks


Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis


Towards Enhancing Relational Rules for Knowledge Graph Link Prediction


Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach


Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study


Towards Enriched Controllability for Educational Question Generation


Towards Entity Alignment in the Open World: An Unsupervised Approach


Towards Entropic Constraints on Quantum Speedups


Towards Environment-Aware 6G Communications via Channel Knowledge Map


Towards Environmentally Equitable AI via Geographical Load Balancing


Towards Equipping Transformer with the Ability of Systematic Compositionality


Towards Equitable Representation in Text-to-Image Synthesis Models with the Cross-Cultural Understanding Benchmark (CCUB) Dataset


Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation


Towards Ethical Content-Based Detection of Online Influence Campaigns


Towards Evaluating Explanations of Vision Transformers for Medical Imaging


Towards Evaluating Generalist Agents: An Automated Benchmark in Open World


Towards Evaluating and Building Versatile Large Language Models for Medicine


Towards Evaluating and Training Verifiably Robust Neural Networks


Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack


Towards Evaluating the Robustness of Neural Networks Learned by Transduction


Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes


Towards Event Extraction from Speech with Contextual Clues


Towards Event-oriented Long Video Understanding


Towards Exact Computation of Inductive Bias


Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization


Towards Explainability in Legal Outcome Prediction Models


Towards Explainable 3D Grounded Visual Question Answering: A New Benchmark and Strong Baseline


Towards Explainable Collaborative Filtering with Taste Clusters Learning


Towards Explainable Conversational Recommender Systems


Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network


Towards Explainable Evaluation Metrics for Natural Language Generation


Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models


Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approach


Towards Explainable LiDAR Point Cloud Semantic Segmentation via Gradient Based Target Localization


Towards Explainable Motion Prediction using Heterogeneous Graph Representations


Towards Explainable Multimodal Depression Recognition for Clinical Interviews


Towards Explainable Real Estate Valuation via Evolutionary Algorithms


Towards Explainable Temporal Reasoning in Large Language Models: A Structure-Aware Generative Framework


Towards Explainable Temporal User Profiling with LLMs


Towards Explainable Traffic Flow Prediction with Large Language Models


Towards Explainable and Interpretable Musical Difficulty Estimation: A Parameter-efficient Approach


Towards Explaining Demographic Bias through the Eyes of Face Recognition Models


Towards Explaining Hypercomplex Neural Networks


Towards Explaining STEM Document Classification using Mathematical Entity Linking


Towards Explaining Subjective Ground of Individuals on Social Media


Towards Exploiting Background Knowledge for Building Conversation Systems


Towards Exploring Fairness in Visual Transformer based Natural and GAN Image Detection Systems


Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark


Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Prior


Towards Face Encryption by Generating Adversarial Identity Masks


Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach


Towards Fair Allocation in Social Commerce Platforms


Towards Fair Evaluation of Dialogue State Tracking by Flexible Incorporation of Turn-level Performances


Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation


Towards Fair Graph Federated Learning via Incentive Mechanisms


Towards Fair Graph Neural Networks via Graph Counterfactual


Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation Embeddings


Towards Fair Pay and Equal Work: Imposing View Time Limits in Crowdsourced Image Classification


Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation


Towards Fair and Efficient Learning-based Congestion Control


Towards Fair and Efficient Public Transportation: A Bus Stop Model


Towards Fair and Privacy-Aware Transfer Learning for Educational Predictive Modeling: A Case Study on Retention Prediction in Community Colleges


Towards Fair and Privacy-Preserving Federated Deep Models


Towards Fairness in Online Service with k Servers and its Application on Fair Food Delivery


Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation


Towards Fairness-Aware Adversarial Learning


Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery


Towards Faithful Natural Language Explanations: A Study Using Activation Patching in Large Language Models


Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering


Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval


Towards Fast Graph Generation via Autoregressive Noisy Filtration Modeling


Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters


Towards Fast Region Adaptive Ultrasound Beamformer for Plane Wave Imaging Using Convolutional Neural Networks


Towards Fast and Accurate Image-Text Retrieval with Self-Supervised Fine-Grained Alignment


Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor


Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians


Towards Faster Decentralized Stochastic Optimization with Communication Compression


Towards Faster Graph Partitioning via Pre-training and Inductive Inference


Towards Faster and More Compact Foundation Models for Molecular Property Prediction


Towards Fault Tolerance in Multi-Agent Reinforcement Learning


Towards Feasible Counterfactual Explanations: A Taxonomy Guided Template-based NLG Method


Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers


Towards Feature Space Adversarial Attack


Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning


Towards Federated Learning With Byzantine-Robust Client Weighting


Towards Federated Learning against Noisy Labels via Local Self-Regularization


Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient ?


Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning


Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi


Towards Few-shot Entity Recognition in Document Images: A Graph Neural Network Approach Robust to Image Manipulation


Towards Few-shot Entity Recognition in Document Images: A Label-aware Sequence-to-Sequence Framework


Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approach


Towards Few-shot Self-explaining Graph Neural Networks


Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation


Towards Filling the Gap in Conversational Search: From Passage Retrieval to Conversational Response Generation


Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network


Towards Fine-Grained Localization of Privacy Behaviors


Towards Fine-Grained Reasoning for Fake News Detection


Towards Fine-Grained Scalability for Stateful Stream Processing Systems


Towards Fine-grained 3D Face Dense Registration: An Optimal Dividing and Diffusing Method


Towards Fine-grained Causal Reasoning and QA


Towards Fine-grained Image Classification with Generative Adversarial Networks and Facial Landmark Detection


Towards Fine-grained Large Object Segmentation 1st Place Solution to 3D AI Challenge 2020 -- Instance Segmentation Track


Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling


Towards Flexibility and Interpretability of Gaussian Process State-Space Model


Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object Detection


Towards Flexible Blind JPEG Artifacts Removal


Towards Flexible Evaluation for Generative Visual Question Answering


Towards Flexible Multi-modal Document Models


Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via Rank Regression


Towards Flops-constrained Face Recognition


Towards Formalising Schutz' Axioms for Minkowski Spacetime in Isabelle/HOL


Towards Formally Verified Compilation of Tag-Based Policy Enforcement


Towards Foundation Model for Chemical Reactor Modeling: Meta-Learning with Physics-Informed Adaptation


Towards Foundation Models for 3D Vision: How Close Are We?


Towards Foundation Time Series Model: To Synthesize Or Not To Synthesize?


Towards Foundational AI Models for Additive Manufacturing: Language Models for G-Code Debugging, Manipulation, and Comprehension


Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets


Towards Frame Rate Agnostic Multi-Object Tracking


Towards Full-Fledged Argument Search: A Framework for Extracting and Clustering Arguments from Unstructured Text


Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving


Towards Fully Automated Manga Translation


Towards Further Understanding of Sparse Filtering via Information Bottleneck


Towards Galaxy Foundation Models with Hybrid Contrastive Learning


Towards General Error Diagnosis via Behavioral Testing in Machine Translation


Towards General Low-Light Raw Noise Synthesis and Modeling


Towards General Negotiation Strategies with End-to-End Reinforcement Learning


Towards General Robustness Verification of MaxPool-based Convolutional Neural Networks via Tightening Linear Approximation


Towards General Text-guided Image Synthesis for Customized Multimodal Brain MRI Generation


Towards General Visual-Linguistic Face Forgery Detection(V2)


Towards General and Efficient Active Learning


Towards General-Purpose Representation Learning of Polygonal Geometries


Towards Generalisable Time Series Understanding Across Domains


Towards Generalising Neural Topical Representations


Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data


Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing


Towards Generalizable Detection of Urgency of Discussion Forum Posts


Towards Generalizable Diabetic Retinopathy Grading in Unseen Domains


Towards Generalizable Multi-Camera 3D Object Detection via Perspective Debiasing


Towards Generalizable Multi-Object Tracking


Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy


Towards Generalizable SER: Soft Labeling and Data Augmentation for Modeling Temporal Emotion Shifts in Large-Scale Multilingual Speech


Towards Generalizable Scene Change Detection


Towards Generalizable Vision-Language Robotic Manipulation: A Benchmark and LLM-guided 3D Policy


Towards Generalizable and Faithful Logic Reasoning over Natural Language via Resolution Refutation


Towards Generalization in Subitizing with Neuro-Symbolic Loss using Holographic Reduced Representations


Towards Generalized Few-Shot Open-Set Object Detection


Towards Generating Ambisonics Using Audio-Visual Cue for Virtual Reality


Towards Generating Benchmark Datasets for Worm Infection Studies


Towards Generating Hop-constrained s-t Simple Path Graphs


Towards Generating Realistic 3D Semantic Training Data for Autonomous Driving


Towards Generative Class Prompt Learning for Fine-grained Visual Recognition


Towards Generative Modeling of Urban Flow through Knowledge-enhanced Denoising Diffusion


Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead


Towards Generic Deobfuscation of Windows API Calls


Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning


Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation


Towards Generic and Controllable Attacks Against Object Detection


Towards Geospatial Foundation Models via Continual Pretraining


Towards Global AI Inclusivity: A Large-Scale Multilingual Terminology Dataset (GIST)


Towards Global Localization using Multi-Modal Object-Instance Re-Identification


Towards Goal-oriented Prompt Engineering for Large Language Models: A Survey


Towards Good Practices for Missing Modality Robust Action Recognition


Towards Good Practices of U-Net for Traffic Forecasting


Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond


Towards Grand Unification of Object Tracking


Towards Graph Representation Learning Based Surgical Workflow Anticipation


Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation


Towards Greener Data Centers via Programmable Data Plane


Towards Ground Truth Explainability on Tabular Data


Towards Ground-truth-free Evaluation of Any Segmentation in Medical Images


Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection


Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning


Towards Harmless Rawlsian Fairness Regardless of Demographic Prior


Towards Harnessing Large Language Models for Comprehension of Conversational Grounding


Towards Hate Speech Detection at Large via Deep Generative Modeling


Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox


Towards Hierarchical Multi-Agent Workflows for Zero-Shot Prompt Optimization


Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language Models


Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning


Towards High Fidelity Face Relighting with Realistic Shadows


Towards High Performance Human Keypoint Detection


Towards High-Level Modelling in Automated Planning


Towards High-Order Complementary Recommendation via Logical Reasoning Network


Towards High-Quality 3D Motion Transfer with Realistic Apparel Animation


Towards High-Quality Specular Highlight Removal by Leveraging Large-Scale Synthetic Data


Towards High-Quality Temporal Action Detection with Sparse Proposals


Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting


Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects


Towards High-Resolution Salient Object Detection


Towards Higher Pareto Frontier in Multilingual Machine Translation


Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos


Towards Highly Realistic Artistic Style Transfer via Stable Diffusion with Step-aware and Layer-aware Prompt


Towards Holistic Visual Quality Assessment of AI-Generated Videos: A LLM-Based Multi-Dimensional Evaluation Model


Towards Human Cognition: Visual Context Guides Syntactic Priming in Fusion-Encoded Models


Towards Human-AI Complementarity with Prediction Sets


Towards Human-Bot Collaborative Software Architecting with ChatGPT


Towards Human-Level 3D Relative Pose Estimation: Generalizable, Training-Free, with Single Reference


Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning


Towards Human-Level Text Coding with LLMs: The Case of Fatherhood Roles in Public Policy Documents


Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations


Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network


Towards Hyper-parameter-free Federated Learning


Towards IID representation learning and its application on biomedical data


Towards Identity-Aware Cross-Modal Retrieval: a Dataset and a Baseline


Towards Image Ambient Lighting Normalization


Towards Image Semantics and Syntax Sequence Learning


Towards Imperceptible Backdoor Attack in Self-supervised Learning


Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions


Towards Implicit Text-Guided 3D Shape Generation


Towards Improved Illicit Node Detection with Positive-Unlabelled Learning


Towards Improved Input Masking for Convolutional Neural Networks


Towards Improved Proxy-based Deep Metric Learning via Data-Augmented Domain Adaptation


Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping


Towards Improving Adversarial Training of NLP Models


Towards Improving Document Understanding: An Exploration on Text-Grounding via MLLMs


Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors


Towards Improving Faithfulness in Abstractive Summarization


Towards Improving Harmonic Sensitivity and Prediction Stability for Singing Melody Extraction


Towards Improving Solution Dominance with Incomparability Conditions: A case-study using Generator Itemset Mining


Towards Improving Spatiotemporal Action Recognition in Videos


Towards Improving the Explainability of Text-based Information Retrieval with Knowledge Graphs


Towards Improving the Generation Quality of Autoregressive Slot VAEs


Towards In-the-wild 3D Plane Reconstruction from a Single Image


Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languages


Towards Incremental Transformers: An Empirical Analysis of Transformer Models for Incremental NLU


Towards Individual Grevy's Zebra Identification via Deep 3D Fitting and Metric Learning


Towards Infusing Auxiliary Knowledge for Distracted Driver Detection


Towards Inheritable Models for Open-Set Domain Adaptation


Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)


Towards Instance-adaptive Inference for Federated Learning


Towards Integration of Discriminability and Robustness for Document-Level Relation Extraction


Towards Intelligent Load Balancing in Data Centers


Towards Intelligent Reconfigurable Wireless Physical Layer (PHY)


Towards Intelligibility-Oriented Audio-Visual Speech Enhancement


Towards Interactive Autonomous Vehicle Testing: Vehicle-Under-Test-Centered Traffic Simulation


Towards Interactive Image Inpainting via Sketch Refinement


Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework


Towards Interactive, Adaptive and Result-aware Big Data Analytics


Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines"


Towards International Relations Data Science: Mining the CIA World Factbook


Towards Interpretable Deep Metric Learning with Structural Matching


Towards Interpretable Deep Networks for Monocular Depth Estimation


Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales


Towards Interpretable Natural Language Understanding with Explanations as Latent Variables


Towards Interpretable Protein Structure Prediction with Sparse Autoencoders


Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAG


Towards Interpretable Reasoning over Paragraph Effects in Situation


Towards Interpretable Sequence Continuation: Analyzing Shared Circuits in Large Language Models


Towards Interpretable Solar Flare Prediction with Attention-based Deep Neural Networks


Towards Interpretable Summary Evaluation via Allocation of Contextual Embeddings to Reference Text Topics


Towards Interpretable Time Series Foundation Models


Towards Interpretable Video Super-Resolution via Alternating Optimization


Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation


Towards Interpreting BERT for Reading Comprehension Based QA


Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction


Towards Interpreting Visual Information Processing in Vision-Language Models


Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation


Towards Invisible Backdoor Attack on Text-to-Image Diffusion Model


Towards Jacamo-rest: A Resource-Oriented Abstraction for Managing Multi-Agent Systems


Towards Job-Transition-Tag Graph for a Better Job Title Representation Learning


Towards Joint Modeling of Dialogue Response and Speech Synthesis based on Large Language Model


Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusion


Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks


Towards Knowledge-Based Recommender Dialog System


Towards Knowledge-Infused Automated Disease Diagnosis Assistant


Towards Knowledge-driven Autonomous Driving


Towards LLM-Empowered Fine-Grained Speech Descriptors for Explainable Emotion Recognition


Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method


Towards LLM-driven Dialogue State Tracking


Towards Label-Efficient Incremental Learning: A Survey


Towards Label-free Scene Understanding by Vision Foundation Models


Towards Landau-Ginzburg models for cominuscule spaces via the exceptional cominuscule family


Towards Language Models That Can See: Computer Vision Through the LENS of Natural Language


Towards Language-Driven Video Inpainting via Multimodal Large Language Models


Towards Language-guided Visual Recognition via Dynamic Convolutions


Towards Large Certified Radius in Randomized Smoothing using Quasiconcave Optimization


Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance


Towards Large-Scale Incremental Dense Mapping using Robot-centric Implicit Neural Representation


Towards Large-Scale Interpretable Knowledge Graph Reasoning for Dialogue Systems


Towards Large-Scale Training of Pathology Foundation Models


Towards Large-scale Building Attribute Mapping using Crowdsourced Images: Scene Text Recognition on Flickr and Problems to be Solved


Towards Large-scale Functional Verification of Universal Quantum Circuits


Towards Last-layer Retraining for Group Robustness with Fewer Annotations


Towards Latent Masked Image Modeling for Self-Supervised Visual Representation Learning


Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models


Towards Learning High-Precision Least Squares Algorithms with Sequence Models


Towards Learning Instantiated Logical Rules from Knowledge Graphs


Towards Learning Monocular 3D Object Localization From 2D Labels using the Physical Laws of Motion


Towards Learning Structure via Consensus for Face Segmentation and Parsing


Towards Learning Universal, Regional, and Local Hydrological Behaviors via Machine-Learning Applied to Large-Sample Datasets


Towards Learning a Universal Non-Semantic Representation of Speech


Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks


Towards Legally Enforceable Hate Speech Detection for Public Forums


Towards Less Constrained Macro-Neural Architecture Search


Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness


Towards Lifelong Learning of Large Language Models: A Survey


Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation


Towards Lighter and Robust Evaluation for Retrieval Augmented Generation


Towards Lightweight Black-Box Attacks against Deep Neural Networks


Towards Lightweight Cross-domain Sequential Recommendation via External Attention-enhanced Graph Convolution Network


Towards Lightweight Data Integration using Multi-workflow Provenance and Data Observability


Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional Network


Towards Lightweight Super-Resolution with Dual Regression Learning


Towards Lightweight Transformer via Group-wise Transformation for Vision-and-Language Tasks


Towards Lithuanian grammatical error correction


Towards Local Visual Modeling for Image Captioning


Towards Localized Fine-Grained Control for Facial Expression Generation


Towards Logically Sound Natural Language Reasoning with Logic-Enhanced Language Model Agents


Towards Long Term SLAM on Thermal Imagery


Towards Long-term Fairness in Recommendation


Towards Lossless ANN-SNN Conversion under Ultra-Low Latency with Dual-Phase Optimization


Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching


Towards Lossless Implicit Neural Representation via Bit Plane Decomposition


Towards Lossless Token Pruning in Late-Interaction Retrieval Models


Towards Low-Energy Adaptive Personalization for Resource-Constrained Devices


Towards Low-Latency Event Stream-based Visual Object Tracking: A Slow-Fast Approach


Towards Low-Resource Harmful Meme Detection with LMM Agents


Towards Low-Resource StarGAN Voice Conversion using Weight Adaptive Instance Normalization


Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks


Towards Low-level Cryptographic Primitives for JavaCards


Towards Lower Bounds on the Depth of ReLU Neural Networks


Towards MRI-Based Autonomous Robotic US Acquisitions: A First Feasibility Study


Towards Machine Learning on data from Professional Cyclists


Towards Machine Learning-Enabled Context Adaption for Reliable Aerial Mesh Routing


Towards Machine Translation for the Kurdish Language


Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems


Towards Machine-Generated Code for the Resolution of User Intentions


Towards Machine-actionable FAIR Digital Objects with a Typing Model that Enables Operations


Towards Macro-AUC oriented Imbalanced Multi-Label Continual Learning


Towards Making Deep Learning-based Vulnerability Detectors Robust


Towards Making Flowchart Images Machine Interpretable


Towards Making a Trojan-horse Attack on Text-to-Image Retrieval


Towards Making the Most of BERT in Neural Machine Translation


Towards Making the Most of ChatGPT for Machine Translation


Towards Making the Most of Dialogue Characteristics for Neural Chat Translation


Towards Mapping Control Theory and Software Engineering Properties using Specification Patterns


Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples


Towards Measuring Representational Similarity of Large Language Models


Towards Measuring and Modeling "Culture" in LLMs: A Survey


Towards Measuring the Impact of Technical Debt on Lead Time: An Industrial Case Study


Towards Mechanised Proofs in Double-Pushout Graph Transformation


Towards Mechanistic Interpretability of Graph Transformers via Attention Graphs


Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining


Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks


Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation


Towards Meta-Pruning via Optimal Transport


Towards Metamerism via Foveated Style Transfer


Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms


Towards Metrical Reconstruction of Human Faces


Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware


Towards Mitigating Architecture Overfitting on Distilled Datasets


Towards Mixed-Criticality Software Architectures for Centralized HPC Platforms in Software-Defined Vehicles: A Systematic Literature Review


Towards Modality Generalization: A Benchmark and Prospective Analysis


Towards Mode Balancing of Generative Models via Diversity Weights


Towards Model Discovery Using Domain Decomposition and PINNs


Towards Model-Agnostic Dataset Condensation by Heterogeneous Models


Towards Model-Agnostic Federated Learning over Networks


Towards Model-Based Data Acquisition for Subjective Multi-Task NLP Problems


Towards Model-based Reinforcement Learning for Industry-near Environments


Towards Modeling Data Quality and Machine Learning Model Performance


Towards Modeling Learner Performance with Large Language Models


Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning


Towards More Accurate Personalized Image Generation: Addressing Overfitting and Evaluation Bias


Towards More Accurate Prediction of Human Empathy and Emotion in Text and Multi-turn Conversations by Combining Advanced NLP, Transformers-based Networks, and Linguistic Methodologies


Towards More Efficient EfficientDets and Low-Light Real-Time Marine Debris Detection


Towards More Efficient Insertion Transformer with Fractional Positional Encoding


Towards More Equitable Question Answering Systems: How Much More Data Do You Need?


Towards More Faithful Natural Language Explanation Using Multi-Level Contrastive Learning in VQA


Towards More Fine-grained and Reliable NLP Performance Prediction


Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark


Towards More Realistic Evaluation for Neural Test Oracle Generation


Towards More Realistic Extraction Attacks: An Adversarial Perspective


Towards More Robust Interpretation via Local Gradient Alignment


Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks


Towards More Trustworthy Deep Code Models by Enabling Out-of-Distribution Detection


Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?


Towards Multi-Granularity Memory Association and Selection for Long-Term Conversational Agents


Towards Multi-Modal Animal Pose Estimation: A Survey and In-Depth Analysis


Towards Multi-Modal Sarcasm Detection via Hierarchical Congruity Modeling with Knowledge Enhancement


Towards Multi-Morphology Controllers with Diversity and Knowledge Distillation


Towards Multi-Sense Cross-Lingual Alignment of Contextual Embeddings


Towards Multi-User Activity Recognition through Facilitated Training Data and Deep Learning for Human-Robot Collaboration Applications


Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphs


Towards Multi-modal Transformers in Federated Learning


Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound


Towards Multilingual Audio-Visual Question Answering


Towards Multimodal Emotional Support Conversation Systems


Towards Multimodal Simultaneous Neural Machine Translation


Towards Multimodal Video Paragraph Captioning Models Robust to Missing Modality


Towards Multiple References Era -- Addressing Data Leakage and Limited Reference Diversity in NLG Evaluation


Towards NNGP-guided Neural Architecture Search


Towards Natural Image Matting in the Wild via Real-Scenario Prior


Towards Natural Language-Based Visualization Authoring


Towards Natural Language-Guided Drones: GeoText-1652 Benchmark with Spatial Relation Matching


Towards Near-imperceptible Steganographic Text


Towards Network Data Analytics in 5G Systems and Beyond


Towards Neural Network based Cognitive Models of Dynamic Decision-Making by Humans


Towards Neural Numeric-To-Text Generation From Temporal Personal Health Data


Towards Neural Scaling Laws for Foundation Models on Temporal Graphs


Towards Neural Scaling Laws for Time Series Foundation Models


Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphs


Towards New Liquid Crystal Phases of DNA mesogens


Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond


Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMs


Towards Next-Generation Steganalysis: LLMs Unleash the Power of Detecting Steganography


Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search


Towards Non-Robocentric Dynamic Landing of Quadrotor UAVs


Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies


Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding


Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction


Towards Novel Target Discovery Through Open-Set Domain Adaptation


Towards Objective and Unbiased Decision Assessments with LLM-Enhanced Hierarchical Attention Networks


Towards Objectively Benchmarking Social Intelligence for Language Agents at Action Level


Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems


Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and Posts


Towards Omni-generalizable Neural Methods for Vehicle Routing Problems


Towards Omni-supervised Referring Expression Segmentation


Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint


Towards One-Shot Learning for Text Classification using Inductive Logic Programming


Towards Online Multi-Modal Social Interaction Understanding


Towards Online Steering of Flame Spray Pyrolysis Nanoparticle Synthesis


Towards Ontology-Enhanced Representation Learning for Large Language Models


Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning


Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation


Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking


Towards Open Temporal Graph Neural Networks


Towards Open Vocabulary Learning: A Survey


Towards Open-Ended Visual Recognition with Large Language Model


Towards Open-Source and Modular Space Systems with ATMOS


Towards Open-Vocabulary Audio-Visual Event Localization


Towards Open-Vocabulary Remote Sensing Image Semantic Segmentation


Towards Open-Vocabulary Video Semantic Segmentation


Towards Open-World Co-Salient Object Detection with Generative Uncertainty-aware Group Selective Exchange-Masking


Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach


Towards Open-World Product Attribute Mining: A Lightly-Supervised Approach


Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models


Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach


Towards Open-World Segmentation of Parts


Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach


Towards Optimal Circuit Generation: Multi-Agent Collaboration Meets Collective Intelligence


Towards Optimal Correlational Object Search


Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection


Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed


Towards Optimal Grammars for RNA Structures


Towards Optimal Offline Reinforcement Learning


Towards Optimal Patch Size in Vision Transformers for Tumor Segmentation


Towards Optimal Power Control via Ensembling Deep Neural Networks


Towards Optimal Prior-Free Permissionless Rebate Mechanisms, with applications to Automated Market Makers & Combinatorial Orderflow Auctions


Towards Optimal Structured CNN Pruning via Generative Adversarial Learning


Towards Optimal Use of Exception Handling Information for Function Detection


Towards Optimally Efficient Search with Deep Learning for Large-Scale MIMO Systems


Towards Optimally Weighted Physics-Informed Neural Networks in Ocean Modelling


Towards Optimising EEG Decoding using Post-hoc Explanations and Domain Knowledge


Towards Optimizing a Convex Cover of Collision-Free Space for Trajectory Generation


Towards Out-of-Distribution Adversarial Robustness


Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment


Towards Painless Policy Optimization for Constrained MDPs


Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video Grounding


Towards Parsimonious Generative Modeling of RNA Families


Towards Patronizing and Condescending Language in Chinese Videos: A Multimodal Dataset and Detector


Towards Pedestrian Detection Using RetinaNet in ECCV 2018 Wider Pedestrian Detection Challenge


Towards Perceiving Small Visual Details in Zero-shot Visual Question Answering with Multimodal LLMs


Towards Perceptually Optimized End-to-end Adaptive Video Streaming


Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems


Towards Persona-Based Empathetic Conversational Models


Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling


Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform


Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders


Towards Physical Plausibility in Neuroevolution Systems


Towards Physically Consistent Deep Learning For Climate Model Parameterizations


Towards Positive Jacobian: Learn to Postprocess Diffeomorphic Image Registration with Matrix Exponential


Towards Practical 2D Grapevine Bud Detection with Fully Convolutional Networks


Towards Practical Alzheimer's Disease Diagnosis: A Lightweight and Interpretable Spiking Neural Model


Towards Practical Control of Singular Values of Convolutional Layers


Towards Practical Federated Causal Structure Learning


Towards Practical Few-Shot Query Sets: Transductive Minimum Description Length Inference


Towards Practical Lottery Ticket Hypothesis for Adversarial Training


Towards Practical Mean Bounds for Small Samples


Towards Practical Multi-Robot Hybrid Tasks Allocation for Autonomous Cleaning


Towards Practical Plug-and-Play Diffusion Models


Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes


Towards Practical Robustness Analysis for DNNs based on PAC-Model Learning


Towards Pragmatic Semantic Image Synthesis for Urban Scenes


Towards Precise 3D Human Pose Estimation with Multi-Perspective Spatial-Temporal Relational Transformers


Towards Precision in Appearance-based Gaze Estimation in the Wild


Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation


Towards Predicting Temporal Changes in a Patient's Chest X-ray Images based on Electronic Health Records


Towards Prediction of Financial Crashes with a D-Wave Quantum Computer


Towards Preemptive Detection of Depression and Anxiety in Twitter


Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet


Towards Principled Learning for Re-ranking in Recommender Systems


Towards Principled User-side Recommender Systems


Towards Principled, Practical Policy Gradient for Bandits and Tabular MDPs


Towards Privacy-Aware Causal Structure Learning in Federated Setting


Towards Privacy-Aware Sign Language Translation at Scale


Towards Privacy-Preserving, Real-Time and Lossless Feature Matching


Towards Privacy-Supporting Fall Detection via Deep Unsupervised RGB2Depth Adaptation


Towards Proactively Forecasting Sentence-Specific Information Popularity within Online News Documents


Towards Probabilistic Session-Type Monitoring


Towards Probabilistic Verification of Machine Unlearning


Towards Probabilistically-Sound Beam Search with Masked Language Models


Towards Probing Speech-Specific Risks in Large Multimodal Models: A Taxonomy, Benchmark, and Insights


Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information


Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detection


Towards Proper Contrastive Self-supervised Learning Strategies For Music Audio Representation


Towards Proxy Staking Accounts Based on NFTs in Ethereum


Towards Quality Assurance of Software Product Lines with Adversarial Configurations


Towards Quantifiable Dialogue Coherence Evaluation


Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement


Towards Quantifying Sampling Bias in Network Inference


Towards Quantifying the Hessian Structure of Neural Networks


Towards Quantitative Evaluation of Crystal Structure Prediction Performance


Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework


Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction


Towards Query Efficient Black-box Attacks: An Input-free Perspective


Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent


Towards Question-based Recommender Systems


Towards RAW Object Detection in Diverse Conditions


Towards RNA life on Early Earth: From atmospheric HCN to biomolecule production in warm little ponds


Towards Rationality in Language and Multimodal Agents: A Survey


Towards Real-Time Advancement of Underwater Visual Quality with GAN


Towards Real-Time Analysis of Broadcast Badminton Videos


Towards Real-Time Panoptic Narrative Grounding by an End-to-End Grounding Network


Towards Real-Time Temporal Graph Learning


Towards Real-Time Text2Video via CLIP-Guided, Pixel-Level Optimization


Towards Real-World Adverse Weather Image Restoration: Enhancing Clearness and Semantics with Vision-Language Models


Towards Real-World Aerial Vision Guidance with Categorical 6D Pose Tracker


Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery Framework


Towards Real-World Blind Face Restoration with Generative Diffusion Prior


Towards Real-World Blind Face Restoration with Generative Facial Prior


Towards Real-World Burst Image Super-Resolution: Benchmark and Method


Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control


Towards Real-World Efficiency: Domain Randomization in Reinforcement Learning for Pre-Capture of Free-Floating Moving Targets by Autonomous Robots


Towards Real-World Focus Stacking with Deep Learning


Towards Real-World HDR Video Reconstruction: A Large-Scale Benchmark Dataset and A Two-Stage Alignment Network


Towards Real-World Prohibited Item Detection: A Large-Scale X-ray Benchmark


Towards Real-World Test-Time Adaptation: Tri-Net Self-Training with Balanced Normalization


Towards Real-World Video Deblurring by Exploring Blur Formation Process


Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters


Towards Real-time Traffic Sign and Traffic Light Detection on Embedded Systems


Towards Real-time Video Compressive Sensing on Mobile Devices


Towards Real-world Event-guided Low-light Video Enhancement and Deblurring


Towards Real-world X-ray Security Inspection: A High-Quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection


Towards Realistic Generative 3D Face Models


Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation


Towards Realistic Low-Light Image Enhancement via ISP Driven Data Modeling


Towards Realistic Low-resource Relation Extraction: A Benchmark with Empirical Baseline Study


Towards Realistic Mechanisms That Incentivize Federated Participation and Contribution


Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD Detection


Towards Realistic Scene Generation with LiDAR Diffusion Models


Towards Realistic Semi-Supervised Learning


Towards Realistic Single-Task Continuous Learning Research for NER


Towards Realistic Ultrasound Fetal Brain Imaging Synthesis


Towards Realistic Underwater Dataset Generation and Color Restoration


Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment


Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias


Towards Reasonably-Sized Character-Level Transformer NMT by Finetuning Subword Systems


Towards Reasoning in Large Language Models via Multi-Agent Peer Review Collaboration


Towards Reasoning in Large Language Models: A Survey


Towards Recognizing Phrase Translation Processes: Experiments on English-French


Towards Recognizing Unseen Categories in Unseen Domains


Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy


Towards Redundancy-Free Sub-networks in Continual Learning


Towards Rehearsal-Free Continual Relation Extraction: Capturing Within-Task Variance with Adaptive Prompting


Towards Reliable AI Model Deployments: Multiple Input Mixup for Out-of-Distribution Detection


Towards Reliable Advertising Image Generation Using Human Feedback


Towards Reliable Dermatology Evaluation Benchmarks


Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection


Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing


Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction


Towards Reliable Rare Category Analysis on Graphs via Individual Calibration


Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation


Towards Reliable Testing for Multiple Information Retrieval System Comparisons


Towards Reliable and Factual Response Generation: Detecting Unanswerable Questions in Information-Seeking Conversations


Towards Reliable and Interpretable Traffic Crash Pattern Prediction and Safety Interventions Using Customized Large Language Models


Towards Reliable and Scalable Linux Kernel CVE Attribution in Automated Static Firmware Analyses


Towards Representation Learning for Weighting Problems in Design-Based Causal Inference


Towards Reproducible Evaluations for Flying Drone Controllers in Virtual Environments


Towards Resolving Propensity Contradiction in Offline Recommender Learning


Towards Resolving the Challenge of Long-tail Distribution in UAV Images for Object Detection


Towards Responsible AI in Education: Hybrid Recommendation System for K-12 Students Case Study


Towards Retrieval-based Conversational Recommendation


Towards Return Parity in Markov Decision Processes


Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning


Towards Reward Fairness in RLHF: From a Resource Allocation Perspective


Towards Rich Emotions in 3D Avatars: A Text-to-3D Avatar Generation Benchmark


Towards Robust Adaptive Object Detection under Noisy Annotations


Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization


Towards Robust Audio Deepfake Detection: A Evolving Benchmark for Continual Learning


Towards Robust Blind Face Restoration with Codebook Lookup Transformer


Towards Robust Data Hiding Against (JPEG) Compression: A Pseudo-Differentiable Deep Learning Approach


Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures


Towards Robust Detection of Adversarial Examples


Towards Robust Domain Generation Algorithm Classification


Towards Robust Evaluation of Unlearning in LLMs via Data Transformations


Towards Robust Event-based Networks for Nighttime via Unpaired Day-to-Night Event Translation


Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology


Towards Robust Federated Analytics via Differentially Private Measurements of Statistical Heterogeneity


Towards Robust Few-shot Point Cloud Semantic Segmentation


Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks


Towards Robust GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization


Towards Robust General Medical Image Segmentation


Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels


Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain Regularization


Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks


Towards Robust Image-in-Audio Deep Steganography


Towards Robust Instruction Tuning on Multimodal Large Language Models


Towards Robust Interpretable Surrogates for Optimization


Towards Robust Learning to Optimize with Theoretical Guarantees


Towards Robust Model Watermark via Reducing Parametric Vulnerability


Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions


Towards Robust Multi-Modal Reasoning via Model Selection


Towards Robust Multi-UAV Collaboration: MARL with Noise-Resilient Communication and Attention Mechanisms


Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution Shifts


Towards Robust Multimodal Representation: A Unified Approach with Adaptive Experts and Alignment


Towards Robust Multimodal Sentiment Analysis with Incomplete Data


Towards Robust NLG Bias Evaluation with Syntactically-diverse Prompts


Towards Robust Neural Networks via Close-loop Control


Towards Robust Neural Networks via Orthogonal Diversity


Towards Robust Offline Reinforcement Learning under Diverse Data Corruption


Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness


Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularization


Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond


Towards Robust Recommendation: A Review and an Adversarial Robustness Evaluation Library


Towards Robust Referring Image Segmentation


Towards Robust Relational Causal Discovery


Towards Robust Scene Text Image Super-resolution via Explicit Location Enhancement


Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-Learning


Towards Robust Stacked Capsule Autoencoder with Hybrid Adversarial Training


Towards Robust Temporal Reasoning of Large Language Models via a Multi-Hop QA Dataset and Pseudo-Instruction Tuning


Towards Robust Text Retrieval with Progressive Learning


Towards Robust Toxic Content Classification


Towards Robust Transcription: Exploring Noise Injection Strategies for Training Data Augmentation


Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset


Towards Robust Unsupervised Attention Prediction in Autonomous Driving


Towards Robust Unsupervised Disentanglement of Sequential Data -- A Case Study Using Music Audio


Towards Robust Video Object Segmentation with Adaptive Object Calibration


Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution


Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning


Towards Robust Visual Tracking for Unmanned Aerial Vehicle with Tri-Attentional Correlation Filters


Towards Robust and Accurate Myoelectric Controller Design based on Multi-objective Optimization using Evolutionary Computation


Towards Robust and Automatic Hyper-Parameter Tunning


Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation


Towards Robust and Expressive Whole-body Human Pose and Shape Estimation


Towards Robust and Generalizable Training: An Empirical Study of Noisy Slot Filling for Input Perturbations


Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs


Towards Robust and Realistic Human Pose Estimation via WiFi Signals


Towards Robust and Semantically Organised Latent Representations for Unsupervised Text Style Transfer


Towards Robust and Unconstrained Full Range of Rotation Head Pose Estimation


Towards Robust k-Nearest-Neighbor Machine Translation


Towards Robustifying NLI Models Against Lexical Dataset Biases


Towards Robustness Against Natural Language Word Substitutions


Towards Robustness to Label Noise in Text Classification via Noise Modeling


Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes


Towards Rotation Invariance in Object Detection


Towards Routing and Edge Computing in Satellite-Terrestrial Networks: A Column Generation Approach


Towards SSH3: how HTTP/3 improves secure shells


Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach


Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement Learning


Towards Safe Multi-Task Bayesian Optimization


Towards Safe Reinforcement Learning with a Safety Editor Policy


Towards Safe Synthetic Image Generation On the Web: A Multimodal Robust NSFW Defense and Million Scale Dataset


Towards Safer Large Language Models through Machine Unlearning


Towards Safer Pretraining: Analyzing and Filtering Harmful Content in Webscale datasets for Responsible LLMs


Towards Safer Self-Driving Through Great PAIN (Physically Adversarial Intelligent Networks)


Towards Safer Smart Contracts: A Sequence Learning Approach to Detecting Vulnerabilities


Towards Sample Efficient Agents through Algorithmic Alignment


Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors


Towards Sample-efficient Overparameterized Meta-learning


Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network


Towards Scalable AASIST: Refining Graph Attention for Speech Deepfake Detection


Towards Scalable Adaptive Learning with Graph Neural Networks and Reinforcement Learning


Towards Scalable Automated Alignment of LLMs: A Survey


Towards Scalable Foundation Models for Digital Dermatology


Towards Scalable Human-aligned Benchmark for Text-guided Image Editing


Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN


Towards Scalable Verification of Deep Reinforcement Learning


Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenes