Directed Motion and Spatial Coherence in the Cell Nucleus


Directed Network Laplacians and Random Graph Models


Directed differential equation discovery using modified mutation and cross-over operators


Direction Augmentation in the Evaluation of Armed Conflict Predictions


Direction Concentration Learning: Enhancing Congruency in Machine Learning


Direction Specific Ambisonics Source Separation with End-To-End Deep Learning


Direction is what you need: Improving Word Embedding Compression in Large Language Models


Direction of Arrival Correction through Speech Quality Feedback


Direction of Arrival with One Microphone, a few LEGOs, and Non-Negative Matrix Factorization


Direction splitting of $\varphi$-functions in exponential integrators for $d$-dimensional problems in Kronecker form


Direction-Aggregated Attack for Transferable Adversarial Examples


Direction-aware Video Demoireing with Temporal-guided Bilateral Learning


Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms


Directional Connectivity-based Segmentation of Medical Images


Directional Deep Embedding and Appearance Learning for Fast Video Object Segmentation


Directional Detection of Light Dark Matter in Superconductors


Directional Optimism for Safe Linear Bandits


Directional Pruning of Deep Neural Networks


Directional Regularized Tensor Modeling for Video Rain Streaks Removal


Directional coupling detection through cross-distance vectors


Directional genetic differentiation and asymmetric migration


Directionality-Aware Mixture Model Parallel Sampling for Efficient Linear Parameter Varying Dynamical System Learning


Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification


Directly Forecasting Belief for Reinforcement Learning with Delays


Directly Handling Missing Data in Linear Discriminant Analysis for Enhancing Classification Accuracy and Interpretability


Directly Training Joint Energy-Based Models for Conditional Synthesis and Calibrated Prediction of Multi-Attribute Data


Directly tracing the vertical stratification of molecules in protoplanetary disks


Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text


Dirichlet Diffusion Score Model for Biological Sequence Generation


Dirichlet Flow Matching with Applications to DNA Sequence Design


Dirichlet Mechanism for Differentially Private KL Divergence Minimization


Dirichlet Process Gaussian-mixture model: An application to localizing coalescing binary neutron stars with gravitational-wave observations


Dirichlet Pruning for Neural Network Compression


Dirichlet Simplex Nest and Geometric Inference


Dirichlet energy and focusing NLS condensates of minimal intensity


Dirichlet process mixtures of block $g$ priors for model selection and prediction in linear models


Dirichlet-Based Prediction Calibration for Learning with Noisy Labels


Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification


Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning


Dirichlet-based Uncertainty Calibration for Active Domain Adaptation


Dirichlet-tree multinomial mixtures for clustering microbiome compositions


Dirty Pixels: Towards End-to-End Image Processing and Perception


Dirty-Waters: Detecting Software Supply Chain Smells


Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data


Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity


DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution


DisCGen: A Framework for Discourse-Informed Counterspeech Generation


DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization


DisCo Fever: Robust Networks Through Distance Correlation


DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training


DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents


DisCo: Distilled Student Models Co-training for Semi-supervised Text Mining


DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation


DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection


DisCoHead: Audio-and-Video-Driven Talking Head Generation by Disentangled Control of Head Pose and Facial Expressions


DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment


DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors


DisGNet: A Distance Graph Neural Network for Forward Kinematics Learning of Gough-Stewart Platform


DisMech: A Discrete Differential Geometry-based Physical Simulator for Soft Robots and Structures


DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training


DisPose: Disentangling Pose Guidance for Controllable Human Image Animation


DisQ: A Novel Quantum Output State Classification Method on IBM Quantum Computers using OpenPulse


DisTime: Distribution-based Time Representation for Video Large Language Models


DisUnknown: Distilling Unknown Factors for Disentanglement Learning


DisWOT: Student Architecture Search for Distillation WithOut Training


Disaggregated Interventions to Reduce Inequality


Disagreement Concerning Effect-Measure Modification


Disambiguate First Parse Later: Generating Interpretations for Ambiguity Resolution in Semantic Parsing


Disambiguated Node Classification with Graph Neural Networks


Disambiguating Music Artists at Scale with Audio Metric Learning


Disambiguating Reference in Visually Grounded Dialogues through Joint Modeling of Textual and Multimodal Semantic Structures


Disambiguation of Company names via Deep Recurrent Networks


Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach


Disambiguatory Signals are Stronger in Word-initial Positions


DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management


DisasterNets: Embedding Machine Learning in Disaster Mapping


Disc asymmetry characterisation in JWST-observed galaxies at 1 < z < 4


Disc cloaking: Establishing a lower limit to the number density of local compact massive spheroids/bulges and the potential fate of some high-z red nuggets


DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory


DiscSense: Automated Semantic Analysis of Discourse Markers


Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading


Discerning Legitimate Failures From False Alerts: A Study of Chromium's Continuous Integration


Discerning Parallax Amplitude in Astrometric Microlensing


Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications


Discerning and Resolving Knowledge Conflicts through Adaptive Decoding with Contextual Information-Entropy Constraint


Discerning media bias within a network of political allies: an analytic condition for disruption by partisans


Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners


Discharge Summary Hospital Course Summarisation of In Patient Electronic Health Record Text with Clinical Concept Guided Deep Pre-Trained Transformer Models


Discipline Reputation Evaluation Based on PhD Exchange Network


Disclosure and Mitigation of Gender Bias in LLMs


Disclosure risk assessment with Bayesian non-parametric hierarchical modelling


Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling


Disco: A Functional Programming Language for Discrete Mathematics


DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design


DiscoDVT: Generating Long Text with Discourse-Aware Discrete Variational Transformer


DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation Recognition


DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement


DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence


DiscoSense: Commonsense Reasoning with Discourse Connectives


DiscoVista: interpretable visualizations of gene tree discordance


Discogs-VI: A Musical Version Identification Dataset Based on Public Editorial Metadata


Disconnect to Connect: A Data Augmentation Method for Improving Topology Accuracy in Image Segmentation


Disconnected Covariance of 2-point Functions in Large-Scale Structure


Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction


Disconnecting the Dots: Re-Examining the Nature of Stellar "Strings" in the Milky Way


Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle


Discontinuous Constituency and BERT: A Case Study of Dutch


Discontinuous Constituent Parsing as Sequence Labeling


Discontinuous Constituent Parsing with Pointer Networks


Discontinuous Grammar as a Foreign Language


Discontinuous Named Entity Recognition as Maximal Clique Discovery


Discord Questions: A Computational Approach To Diversity Analysis in News Coverage


Discount Factor as a Regularizer in Reinforcement Learning


Discounted Adaptive Online Learning: Towards Better Regularization


Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion


Discourse Coherence in the Wild: A Dataset, Evaluation and Methods


Discourse Comprehension: A Question Answering Framework to Represent Sentence Connections


Discourse Embellishment Using a Deep Encoder-Decoder Network


Discourse Level Factors for Sentence Deletion in Text Simplification


Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference


Discourse Parsing in Videos: A Multi-modal Appraoch


Discourse Probing of Pretrained Language Models


Discourse Relation Embeddings: Representing the Relations between Discourse Segments in Social Media


Discourse Structures Guided Fine-grained Propaganda Identification


Discourse-Aware Neural Extractive Text Summarization


Discover and Cure: Concept-aware Mitigation of Spurious Correlation


Discover and Learn New Objects from Documentaries


Discover and Mitigate Multiple Biased Subgroups in Image Classifiers


Discover and Mitigate Unknown Biases with Debiasing Alternate Networks


Discover the Unknown Biased Attribute of an Image Classifier


Discovering Antagonists in Networks of Systems: Robot Deployment


Discovering Association with Copula Entropy


Discovering Bayesian Market Views for Intelligent Asset Allocation


Discovering Causal Structure with Reproducing-Kernel Hilbert Space $ε$-Machines


Discovering Causality for Efficient Cooperation in Multi-Agent Environments


Discovering Clinically Meaningful Shape Features for the Analysis of Tumor Pathology Images


Discovering Common Information in Multi-view Data


Discovering Concepts in Learned Representations using Statistical Inference and Interactive Visualization


Discovering Conservation Laws using Optimal Transport and Manifold Learning


Discovering Continuous-Time Memory-Based Symbolic Policies using Genetic Programming


Discovering Dense Correlated Subgraphs in Dynamic Networks


Discovering Design Concepts for CAD Sketches


Discovering Differences in the Representation of People using Contextualized Semantic Axes


Discovering Distribution Shifts using Latent Space Representations


Discovering Domain Disentanglement for Generalized Multi-source Domain Adaptation


Discovering Dynamic Causal Space for DAG Structure Learning


Discovering Dynamic Functional Brain Networks via Spatial and Channel-wise Attention


Discovering Dynamic Patterns from Spatiotemporal Data with Time-Varying Low-Rank Autoregression


Discovering Dynamics with Kolmogorov Arnold Networks: Linear Multistep Method-Based Algorithms and Error Estimation


Discovering Effective Policies for Land-Use Planning with Neuroevolution


Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models


Discovering Fair Representations in the Data Domain


Discovering Galaxy Features via Dataset Distillation


Discovering General-Purpose Active Learning Strategies


Discovering Generative Models from Event Logs: Data-driven Simulation vs Deep Learning


Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning


Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning


Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning


Discovering Hierarchical Processes Using Flexible Activity Trees for Event Abstraction


Discovering Highly Influential Shortcut Reasoning: An Automated Template-Free Approach


Discovering Human-Object Interaction Concepts via Self-Compositional Learning


Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity


Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference


Discovering Influential Factors in Variational Autoencoder


Discovering Intrinsic Reward with Contrastive Random Walk


Discovering Invariant Rationales for Graph Neural Networks


Discovering Invariant Spatial Features in Electron Energy Loss Spectroscopy Images on the Mesoscopic and Atomic Levels


Discovering IoT Physical Channel Vulnerabilities


Discovering Knowledge-Critical Subnetworks in Pretrained Language Models


Discovering Language-neutral Sub-networks in Multilingual Language Models


Discovering Latent Knowledge in Language Models Without Supervision


Discovering Latent Themes in Social Media Messaging: A Machine-in-the-Loop Approach Integrating LLMs


Discovering Leitmotifs in Multidimensional Time Series


Discovering Local Hidden-Variable Models for Arbitrary Multipartite Entangled States and Arbitrary Measurements


Discovering Locally Maximal Bipartite Subgraphs


Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels


Discovering Low-rank Subspaces for Language-agnostic Multilingual Representations


Discovering Many Diverse Solutions with Bayesian Optimization


Discovering Mathematical Objects of Interest -- A Study of Mathematical Notations


Discovering Melting Temperature Prediction Models of Inorganic Solids by Combining Supervised and Unsupervised Learning


Discovering Minimal Reinforcement Learning Environments


Discovering Mixtures of Structural Causal Models from Time Series Data


Discovering Multi-Label Actor-Action Association in a Weakly Supervised Setting


Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement


Discovering New Interpretable Conservation Laws as Sparse Invariants


Discovering New Runge-Kutta Methods Using Unstructured Numerical Search


Discovering Nonlinear Relations with Minimum Predictive Information Regularization


Discovering Object Masks with Transformers for Unsupervised Semantic Segmentation


Discovering Object-Centric Generalized Value Functions From Pixels


Discovering PDEs from Multiple Experiments


Discovering Partially Known Ordinary Differential Equations: a Case Study on the Chemical Kinetics of Cellulose Degradation


Discovering Pattern Structure Using Differentiable Compositing


Discovering Physics-Informed Neural Networks Model for Solving Partial Differential Equations through Evolutionary Computation


Discovering Process Models that Support Desired Behavior and Avoid Undesired Behavior


Discovering Reliable Correlations in Categorical Data


Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms


Discovering Representations for Black-box Optimization


Discovering Sensorimotor Agency in Cellular Automata using Diversity Search


Discovering Sparse Interpretable Dynamics from Partial Observations


Discovering Spatio-Temporal Rationales for Video Question Answering


Discovering Spoofing Attempts on Language Model Watermarks


Discovering Strategic Behaviors for Collaborative Content-Production in Social Networks


Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series


Discovering Superhard B-N-O Compounds by Iterative Machine Learning and Evolutionary Structure Predictions


Discovering Symbolic Models from Deep Learning with Inductive Biases


Discovering Textual Structures: Generative Grammar Induction using Template Trees


Discovering Transferable Forensic Features for CNN-generated Images Detection


Discovering Underlying Person Structure Pattern with Relative Local Distance for Person Re-identification


Discovering Universal Geometry in Embeddings with ICA


Discovering User-Interpretable Capabilities of Black-Box Planning Agents


Discovering Utility-driven Interval Rules


Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror


Discovering alignment relations with Graph Convolutional Networks: a biomedical case study


Discovering and Achieving Goals via World Models


Discovering and Categorising Language Biases in Reddit


Discovering and Explaining the Representation Bottleneck of DNNs


Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions


Discovering and Exploiting Sparse Rewards in a Learned Behavior Space


Discovering and Interpreting Biased Concepts in Online Communities


Discovering and Mitigating Visual Biases through Keyword Explanation


Discovering and exploring cases of educational source code plagiarism with Dolos


Discovering and interpreting transcriptomic drivers of imaging traits using neural networks


Discovering care pathways for multi-morbid patients using event graphs


Discovering collective narratives shifts in online discussions


Discovering dynamics and parameters of nonlinear oscillatory and chaotic systems from partial observations


Discovering emergent connections in quantum physics research via dynamic word embeddings


Discovering explicit Reynolds-averaged turbulence closures for turbulent separated flows through deep learning-based symbolic regression with non-linear corrections


Discovering long term dependencies in noisy time series data using deep learning


Discovering modular solutions that generalize compositionally


Discovering new robust local search algorithms with neuro-evolution


Discovering novel cancer bio-markers in acquired lapatinib resistance using Bayesian methods


Discovering strongly lensed quasar candidates with catalogue-based methods from DESI Legacy Surveys


Discovering symbolic expressions with parallelized tree search


Discovering the Elite Hypervolume by Leveraging Interspecies Correlation


Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction


Discovering the Rationale of Decisions: Experiments on Aligning Learning and Reasoning


Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering


Discovering the underlying analytic structure within Standard Model constants using artificial intelligence


Discovery and Recognition of Formula Concepts using Machine Learning


Discovery and Simulation of Data-Aware Business Processes


Discovery and Validation of a High-Density sub-Neptune from the K2 Mission


Discovery and Vetting of Exoplanets I: Benchmarking K2 Vetting Tools


Discovery and inference of a causal network with hidden confounding


Discovery of Critical Thresholds in Mixed Exposures and Estimation of Policy Intervention Effects using Targeted Learning


Discovery of Driving Patterns by Trajectory Segmentation


Discovery of Green's function based on symbolic regression with physical hard constraints


Discovery of High-Velocity H$α$ Emission in the Direction of the Fermi Bubble


Discovery of Jet-Bubble-Disk Interaction: Jet Feedback on a Protoplanetary Disk via an Expanding Bubble in WSB 52


Discovery of Keys for Graphs [Extended Version]


Discovery of Natural Language Concepts in Individual Units of CNNs


Discovery of Nonlinear Multiscale Systems: Sampling Strategies and Embeddings


Discovery of PSR J0523-7125 as a Circularly Polarized Variable Radio Source in the Large Magellanic Cloud


Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models


Discovery of Self-Assembling $π$-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation


Discovery of Single Independent Latent Variable


Discovery of a radio emitting neutron star with an ultra-long spin period of 76 seconds


Discovery of differential equations using sparse state and parameter regression


Discovery of highly anisotropic dielectric crystals with equivariant graph neural networks


Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case


Discovery of new stellar groups in the Orion complex


Discovery of partial differential equations from highly noisy and sparse data with physics-informed information criterion


Discovery of post-mass-transfer helium-burning red giants using asteroseismology


Discovery of sparse hysteresis models for piezoelectric materials


Discovery of the Hidden State in Ionic Models Using a Domain-Specific Recurrent Neural Network


DiscoveryBench: Towards Data-Driven Discovery with Large Language Models


Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous Data


Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image Segmentation


Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects


Discrepancy measures for sensitivity analysis


Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo


Discrete Action On-Policy Learning with Action-Value Critic


Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification


Discrete Auto-regressive Variational Attention Models for Text Modeling


Discrete Codebook World Models for Continuous Control


Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation


Discrete Denoising Diffusion Approach to Integer Factorization


Discrete Dictionary-based Decomposition Layer for Structured Representation Learning


Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution


Discrete Diffusion Probabilistic Models for Symbolic Music Generation


Discrete Diffusion in Large Language and Multimodal Models: A Survey


Discrete Dynamical System Approaches for Boolean Polynomial Optimization


Discrete Exponential-Family Models for Multivariate Binary Outcomes


Discrete Factorization Machines for Fast Feature-based Recommendation


Discrete Function Bases and Convolutional Neural Networks


Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control


Discrete Graph Structure Learning for Forecasting Multiple Time Series


Discrete Hamilton-Jacobi theory for systems with external forces


Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery


Discrete Latent Variable Representations for Low-Resource Text Classification


Discrete Level Set Persistence for Finite Discrete Functions


Discrete Object Generation with Reversible Inductive Construction


Discrete Optimal Designs for Distributed Energy Systems with Nonconvex Multiphase Optimal Power Flow


Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction


Discrete Point Flow Networks for Efficient Point Cloud Generation


Discrete Point-wise Attack Is Not Enough: Generalized Manifold Adversarial Attack for Face Recognition


Discrete Prior-based Temporal-coherent Content Prediction for Blind Face Video Restoration


Discrete Prompt Compression with Reinforcement Learning


Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-ranker


Discrete Rotation Equivariance for Point Cloud Recognition


Discrete Scale-invariant Metric Learning for Efficient Collaborative Filtering


Discrete Semantic Tokenization for Deep CTR Prediction


Discrete Shortest Paths in Optimal Power Flow Feasible Regions


Discrete Signal Processing on Meet/Join Lattices


Discrete State-Action Abstraction via the Successor Representation


Discrete States-Based Trajectory Planning for Nonholonomic Robots


Discrete Vector Calculus and Helmholtz Hodge Decomposition for Classical Finite Difference Summation by Parts Operators


Discrete Wasserstein Barycenters: Optimal Transport for Discrete Data


Discrete and Continuous Difference of Submodular Minimization


Discrete and Soft Prompting for Multilingual Models


Discrete and continuous mathematical models of sharp-fronted collective cell migration and invasion


Discrete and free groups acting on locally finite trees


Discrete and metric divisorial gonality can be different


Discrete approximation of risk-based prices under volatility uncertainty


Discrete element method model of soot aggregates


Discrete geometry of Cox rings of blow-ups of $\mathbb{P}^3$


Discrete gradient methods for port-Hamiltonian differential-algebraic equations


Discrete neural nets and polymorphic learning


Discrete orthogonal polynomials as a tool for detection of small anomalies of time series: a case study of GPS final orbits


Discrete representations in neural models of spoken language


Discrete signature and its application to finance


Discrete symmetries and Efficient Counting of Operators


Discrete transforms of quantized persistence diagrams


Discrete, compositional, and symbolic representations through attractor dynamics


Discrete-Constrained Regression for Local Counting Models


Discrete-Continuous Smoothing and Mapping


Discrete-Time Distribution Steering using Monte Carlo Tree Search


Discrete-Time Open Quantum Walks for Vertex Ranking in Graphs


Discrete-event simulation of quantum walks


Discrete-state Continuous-time Diffusion for Graph Generation


Discrete-to-Deep Supervised Policy Learning


DiscreteZOO: a Fingerprint Database of Discrete Objects


Discretionary Extensions to Unemployment-Insurance Compensation and Some Potential Costs for a McCall Worker


Discretization of Structured Bosonic Environments at Finite Temperature by Interpolative Decomposition: Theory and Application


Discretization of continuous input spaces in the hippocampal autoencoder


Discretization-Dependent Dissolution of (Dis)Continuous Gliders: Non-Platonic Self-Organization in Complex Systems


Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression


Discretization-independent surrogate modeling over complex geometries using hypernetworks and implicit representations


Discretize Relaxed Solution of Spectral Clustering via a Non-Heuristic Algorithm


Discretize first, filter next: learning divergence-consistent closure models for large-eddy simulation


Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows


Discretized Integrated Gradients for Explaining Language Models


Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning


Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective


Discriminating Against Unrealistic Interpolations in Generative Adversarial Networks


Discriminating Quantum States with Quantum Machine Learning


Discrimination through Image Selection by Job Advertisers on Facebook


Discriminative Adversarial Domain Adaptation


Discriminative Appearance Modeling with Multi-track Pooling for Real-time Multi-object Tracking


Discriminative Bayesian filtering lends momentum to the stochastic Newton method for minimizing log-convex functions


Discriminative Class Tokens for Text-to-Image Diffusion Models


Discriminative Clustering with Representation Learning with any Ratio of Labeled to Unlabeled Data


Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection


Discriminative Embeddings of Latent Variable Models for Structured Data


Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment


Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability


Discriminative Feature Learning through Feature Distance Loss


Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data


Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model


Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions


Discriminative Latent Semantic Graph for Video Captioning


Discriminative Multimodal Learning via Conditional Priors in Generative Models


Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference


Discriminative Neural Clustering for Speaker Diarisation


Discriminative Ordering Through Ensemble Consensus


Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations


Discriminative Policy Optimization for Token-Level Reward Models


Discriminative Predicate Path Mining for Fact Checking in Knowledge Graphs


Discriminative Reasoning for Document-level Relation Extraction


Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation


Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation


Discriminative Region-based Multi-Label Zero-Shot Learning


Discriminative Representation learning via Attention-Enhanced Contrastive Learning for Short Text Clustering


Discriminative Sample-Guided and Parameter-Efficient Feature Space Adaptation for Cross-Domain Few-Shot Learning


Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection


Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching


Discriminative Topic Mining via Category-Name Guided Text Embedding


Discriminative Topic Modeling with Logistic LDA


Discriminative Training of VBx Diarization


Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding


Discriminative calibration: Check Bayesian computation from simulations and flexible classifier


Discriminative feature generation for classification of imbalanced data


Discriminatively Learned Hierarchical Rank Pooling Networks


Discriminatively-Tuned Generative Classifiers for Robust Natural Language Inference


Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator


Discriminator Guidance for Autoregressive Diffusion Models


Discriminator-Cooperated Feature Map Distillation for GAN Compression


Discriminator-Free Generative Adversarial Attack


Discriminatory Expressions to Produce Interpretable Models in Short Documents


Discs and outflows in the early phases of massive star formation: influence of magnetic fields and ambipolar diffusion


Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications


Discussion of a uniqueness result in "Equilibrium Configurations for a Floating Drop"


Disease Normalization with Graph Embeddings


Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application to Parkinson's Disease trajectory modelling


Disease State Prediction From Single-Cell Data Using Graph Attention Networks


Disease control as an optimization problem


Disease-informed Adaptation of Vision-Language Models


DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation


DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation


DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction


DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning


DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering


Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal Perspective


Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation


Disentangled Causal Embedding With Contrastive Learning For Recommender System


Disentangled Condensation for Large-scale Graphs


Disentangled Contrastive Collaborative Filtering


Disentangled Contrastive Learning for Learning Robust Textual Representations


Disentangled Cycle Consistency for Highly-realistic Virtual Try-On


Disentangled Diffusion-Based 3D Human Pose Estimation with Hierarchical Spatial and Temporal Denoiser


Disentangled Dynamic Graph Deep Generation


Disentangled Face Attribute Editing via Instance-Aware Latent Space Search


Disentangled Feature Representation for Few-shot Image Classification


Disentangled Generative Models for Robust Prediction of System Dynamics


Disentangled Graph Neural Networks for Session-based Recommendation


Disentangled Graph Social Recommendation


Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation with Interpretability


Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network


Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting


Disentangled Knowledge Tracing for Alleviating Cognitive Bias


Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media


Disentangled Makeup Transfer with Generative Adversarial Network


Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval


Disentangled Modeling of Preferences and Social Influence for Group Recommendation


Disentangled Motion Modeling for Video Frame Interpolation


Disentangled Multi-Fidelity Deep Bayesian Active Learning


Disentangled Multimodal Representation Learning for Recommendation


Disentangled Ontology Embedding for Zero-shot Learning


Disentangled Phonetic Representation for Chinese Spelling Correction


Disentangled Pre-training for Human-Object Interaction Detection


Disentangled Pre-training for Image Matting


Disentangled Representation Learning for 3D Face Shape


Disentangled Representation Learning for Astronomical Chemical Tagging


Disentangled Representation Learning for Environment-agnostic Speaker Recognition


Disentangled Representation Learning for RF Fingerprint Extraction under Unknown Channel Statistics


Disentangled Representation Learning for Text-Video Retrieval


Disentangled Representation Learning in Cardiac Image Analysis


Disentangled Representation for Causal Mediation Analysis


Disentangled Representation for Diversified Recommendations


Disentangled Representations via Synergy Minimization


Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction


Disentangled Sequence to Sequence Learning for Compositional Generalization


Disentangled Source-Free Personalization for Facial Expression Recognition with Neutral Target Data


Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model


Disentangled Variational Autoencoder for Emotion Recognition in Conversations


Disentangled Variational Information Bottleneck for Multiview Representation Learning


Disentangled and Self-Explainable Node Representation Learning


Disentanglement and Generalization Under Correlation Shifts


Disentanglement by Cyclic Reconstruction


Disentanglement of Latent Representations via Causal Interventions


Disentanglement via entanglement: A unified method for Wannier localization


Disentanglement with Factor Quantized Variational Autoencoders


Disentangling 3D Prototypical Networks For Few-Shot Concept Learning


Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning


Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders


Disentangling Content and Motion for Text-Based Neural Video Manipulation


Disentangling Decentralized Finance (DeFi) Compositions


Disentangling Disentanglement in Variational Autoencoders


Disentangling Extraction and Reasoning in Multi-hop Spatial Reasoning


Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov Logic


Disentangling Hate Across Target Identities


Disentangling Heterogeneous Knowledge Concept Embedding for Cognitive Diagnosis on Untested Knowledge


Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Mesh Variational Autoencoder with Contrastive Learning


Disentangling ID and Modality Effects for Session-based Recommendation


Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA


Disentangling Influence: Using Disentangled Representations to Audit Model Predictions


Disentangling Instance and Scene Contexts for 3D Semantic Scene Completion


Disentangling Instructive Information from Ranked Multiple Candidates for Multi-Document Scientific Summarization


Disentangling Interactions and Dependencies in Feature Attribution


Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis


Disentangling Label Distribution for Long-tailed Visual Recognition


Disentangling Language and Knowledge in Task-Oriented Dialogs


Disentangling Learning Representations with Density Estimation


Disentangling Long and Short-Term Interests for Recommendation


Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting


Disentangling Masked Autoencoders for Unsupervised Domain Generalization


Disentangling Mean Embeddings for Better Diagnostics of Image Generators


Disentangling Memory and Reasoning Ability in Large Language Models


Disentangling Motion, Foreground and Background Features in Videos


Disentangling Multi-view Representations Beyond Inductive Bias


Disentangling Multiple Conditional Inputs in GANs


Disentangling Multiple Features in Video Sequences using Gaussian Processes in Variational Autoencoders


Disentangling Neuron Representations with Concept Vectors


Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network


Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth


Disentangling Orthogonal Planes for Indoor Panoramic Room Layout Estimation with Cross-Scale Distortion Awareness


Disentangling Overlapping Astronomical Sources using Spatial and Spectral Information


Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks


Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction


Disentangling Policy from Offline Task Representation Learning via Adversarial Data Augmentation


Disentangling Polysemantic Channels in Convolutional Neural Networks


Disentangling Preference Representation and Text Generation for Efficient Individual Preference Alignment


Disentangling Random and Cyclic Effects in Time-Lapse Sequences


Disentangling Safe and Unsafe Corruptions via Anisotropy and Locality


Disentangling Semantic-to-visual Confusion for Zero-shot Learning


Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models


Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning


Disentangling Speakers in Multi-Talker Speech Recognition with Speaker-Aware CTC


Disentangling Specificity for Abstractive Multi-document Summarization


Disentangling Speech and Non-Speech Components for Building Robust Acoustic Models from Found Data


Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting


Disentangling Tabular Data Towards Better One-Class Anomaly Detection


Disentangling Textual and Acoustic Features of Neural Speech Representations


Disentangling Time Series Spectra with Gaussian Processes: Applications to Radial Velocity Analysis


Disentangling Uncertainties by Learning Compressed Data Representation


Disentangling Uncertainty in Machine Translation Evaluation


Disentangling Visual Embeddings for Attributes and Objects


Disentangling Writer and Character Styles for Handwriting Generation


Disentangling and Generating Modalities for Recommendation in Missing Modality Scenarios


Disentangling and Mitigating the Impact of Task Similarity for Continual Learning


Disentangling discrete and continuous spectra of tidally forced internal waves in shear flow


Disentangling high order effects in the transfer entropy


Disentangling images with Lie group transformations and sparse coding


Disentangling intrinsic motion from neighbourhood effects in heterogeneous collective motion


Disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application


Disentangling positive and negative partisanship in social media interactions using a coevolving latent space network with attractors model


Disentangling representations of retinal images with generative models


Disentangling semantics in language through VAEs and a certain architectural choice


Disentangling shared and private latent factors in multimodal Variational Autoencoders


Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical video


Disentangling the Complex Multiplexed DIA Spectra in De Novo Peptide Sequencing


Disentangling the Effects of Temperature, Clouds, and Gravity on K I doublet in L dwarfs


Disentangling the Halo: Joint Model for Measurements of the Kinetic Sunyaev-Zeldovich Effect and Galaxy-Galaxy Lensing


Disentangling the Impacts of Language and Channel Variability on Speech Separation Networks


Disentangling the Mechanisms Behind Implicit Regularization in SGD


Disentangling the Physics of the Attractive Hubbard Model via the Accessible and Symmetry-Resolved Entanglement Entropies


Disentangling the optical AGN and Host-galaxy luminosity with a probabilistic Flux Variation Gradient


Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks


Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering


DisguisOR: Holistic Face Anonymization for the Operating Room


DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild


Disguised Copyright Infringement of Latent Diffusion Models


Disguising Personal Identity Information in EEG Signals


Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting


Disinformation Capabilities of Large Language Models


Disintegrating Exoplanets: Creating Size Constraints by Statistically Peering Through the Debris


Disjoint Processing Mechanisms of Hierarchical and Linear Grammars in Large Language Models


Disk galaxies and their dark halos as self-organized patterns


Disk-Star Alignment I: Pre-Main-Sequence Stellar Parameters and the Statistical Alignment Between Disks and Stellar Rotation


Disk2Planet: A Robust and Automated Machine Learning Tool for Parameter Inference in Disk-Planet Systems


DiskMINT: A Tool to Estimate Disk Masses with CO Isotopologues


Dislocation Avalanches: Earthquakes on the Micron Scale


Dislocation dynamics in Ni-based superalloys: Parameterising dislocation trajectories from atomistic simulations


Dismai-Bench: Benchmarking and designing generative models using disordered materials and interfaces


Dismantling Complex Networks by a Neural Model Trained from Tiny Networks


Disordered Phase in Ising and Metastability in Cellular Potts Models Hint at Glassy Dynamics


Disordered-DABS: A Benchmark for Dynamic Aspect-Based Summarization in Disordered Texts


Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation


DispFormer: Pretrained Transformer for Flexible Dispersion Curve Inversion from Global Synthesis to Regional Applications


DispaRisk: Auditing Fairness Through Usable Information


Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning


Disparate Impact in Differential Privacy from Gradient Misalignment


Disparate Impact on Group Accuracy of Linearization for Private Inference


Disparities in greenspace access during COVID-19 mobility restrictions


Disparity Between Batches as a Signal for Early Stopping


Disparity Estimation Using a Quad-Pixel Sensor


Disparity Sliding Window: Object Proposals From Disparity Images


Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification


Dispatcher: A Message-Passing Approach To Language Modelling


Dispatching to Parallel Servers: Solutions of Poisson's Equation for First-Policy Improvement


Dispersal-based species pools as sources of connectivity area mismatches


Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction


DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level


Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation


Display of 3D Illuminations using Flying Light Specks


Dispu$τ$able: the high cost of a low optical depth


Dispute-free Scalable Open Vote Network using zk-SNARKs


Disrupt Your Research Using Generative AI Powered ScienceSage


Disrupting Deep Uncertainty Estimation Without Harming Accuracy


Disrupting Diffusion: Token-Level Attention Erasure Attack against Diffusion-based Customization


Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms


Dissected 3D CNNs: Temporal Skip Connections for Efficient Online Video Processing


Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients


Dissecting Adversarial Robustness of Multimodal LM Agents


Dissecting CLIP: Decomposition with a Schur Complement-based Approach


Dissecting Conditional Branch Predictors of Apple Firestorm and Qualcomm Oryon for Software Optimization and Architectural Analysis


Dissecting Dissonance: Benchmarking Large Multimodal Models Against Self-Contradictory Instructions


Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of Ethereum Graph


Dissecting FLOPs along input dimensions for GreenAI cost estimations


Dissecting Fine-Tuning Unlearning in Large Language Models


Dissecting Generation Modes for Abstractive Summarization Models via Ablation and Attribution


Dissecting Language Models: Machine Unlearning via Selective Pruning


Dissecting Logical Reasoning in LLMs: A Fine-Grained Evaluation and Supervision Study


Dissecting Long Reasoning Models: An Empirical Study


Dissecting Multiplication in Transformers: Insights into LLMs


Dissecting Nearby Galaxies with piXedfit: I. Spatially Resolved Properties of Stars, Dust, and Gas as Revealed by Panchromatic SED Fitting


Dissecting Out-of-Distribution Detection and Open-Set Recognition: A Critical Analysis of Methods and Benchmarks


Dissecting Payload-based Transaction Phishing on Ethereum


Dissecting Query-Key Interaction in Vision Transformers


Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI


Dissecting Self-Supervised Learning Methods for Surgical Computer Vision


Dissecting Supervised Contrastive Learning


Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numeric Behaviors


Dissecting graph measure performance for node clustering in LFR parameter space


Dissecting stellar chemical abundance space with t-SNE


Dissecting the Diffusion Process in Linear Graph Convolutional Networks


Dissecting the Failure of Invariant Learning on Graphs


Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers


Dissecting the software-based measurement of CPU energy consumption: a comparative analysis


Dissecting the square into seven or nine congruent parts


Dissecting van der Waals interactions with Density Functional Theory -- Wannier-basis approach


Dissecting vocabulary biases datasets through statistical testing and automated data augmentation for artifact mitigation in Natural Language Inference


Dissimilar Nodes Improve Graph Active Learning


Dissipative Dynamics of Graph-State Stabilizers with Superconducting Qubits


Dissipative Forces in Photon-Medium Interactions Using Perturbation Theory


Dissipative and dispersive cavity optomechanics with a frequency-dependent mirror


Dissipative quadratizations of polynomial ODE systems


Dissipativity and Integral Quadratic Constraints, Tailored computational robustness tests for complex interconnections


Dissipativity-Based Decentralized Co-Design of Distributed Controllers and Communication Topologies for Vehicular Platoons


Dissociating Artificial Intelligence from Artificial Consciousness


Dissociation dynamics of the diamondoid adamantane upon photoionization by XUV femtosecond pulses


Dissociation of Faithful and Unfaithful Reasoning in LLMs


Dissolving Constraints for Riemannian Optimization


Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection


Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint


Dist-PU: Positive-Unlabeled Learning from a Label Distribution Perspective


Dist2Cycle: A Simplicial Neural Network for Homology Localization


DistALANER: Distantly Supervised Active Learning Augmented Named Entity Recognition in the Open Source Software Ecosystem


DistFL: Distribution-aware Federated Learning for Mobile Scenarios


DistFormer: Enhancing Local and Global Features for Monocular Per-Object Distance Estimation


DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification


DistML.js: Installation-free Distributed Deep Learning Framework for Web Browsers


DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials


DistNet: Deep Tracking by displacement regression: application to bacteria growing in the Mother Machine


DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting


DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems


DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving


DistStat.jl: Towards Unified Programming for High-Performance Statistical Computing Environments in Julia


Distance Based Image Classification: A solution to generative classification's conundrum?


Distance Guided Channel Weighting for Semantic Segmentation


Distance Guided Generative Adversarial Network for Explainable Binary Classifications


Distance Matters For Improving Performance Estimation Under Covariate Shift


Distance Matters in Human-Object Interaction Detection


Distance Recomputator and Topology Reconstructor for Graph Neural Networks


Distance and stellar parameter estimations of solar-like stars from the LAMOST spectroscopic survey


Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs


Distance bounds for generalized bicycle codes


Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional Rotation


Distance-Aware Occlusion Detection with Focused Attention


Distance-Aware eXplanation Based Learning


Distance-Based Propagation for Efficient Knowledge Graph Reasoning


Distance-Based Regularisation of Deep Networks for Fine-Tuning


Distance-Based Tree-Sliced Wasserstein Distance


Distance-Ratio-Based Formulation for Metric Learning


Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction


Distance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical Recommendation


Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation


Distance-based mutual congestion feature selection with genetic algorithm for high-dimensional medical datasets


Distance-based resource quantification for sets of quantum measurements


Distance-learning For Approximate Bayesian Computation To Model a Volcanic Eruption


Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification


Distances for Markov Chains, and Their Differentiation


Distant Learning for Entity Linking with Automatic Noise Detection


Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions


Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning


Distantly Supervised Named Entity Recognition via Confidence-Based Multi-Class Positive and Unlabeled Learning


Distantly Supervised Relation Extraction in Federated Settings


Distantly Supervised Relation Extraction via Recursive Hierarchy-Interactive Attention and Entity-Order Perception


Distantly-Supervised Joint Extraction with Noise-Robust Learning


Distantly-Supervised Long-Tailed Relation Extraction Using Constraint Graphs


Distantly-Supervised Named Entity Recognition with Adaptive Teacher Learning and Fine-grained Student Ensemble


Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training


Distantly-Supervised Neural Relation Extraction with Side Information using BERT


Disti-Mator: an entanglement distillation-based state estimator


Distil the informative essence of loop detector data set: Is network-level traffic forecasting hungry for more data?


DistilDIRE: A Small, Fast, Cheap and Lightweight Diffusion Synthesized Deepfake Detection


DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERT


DistilPose: Tokenized Pose Regression with Heatmap Distillation


DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition


DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model


Distill Any Depth: Distillation Creates a Stronger Monocular Depth Estimator


Distill Visual Chart Reasoning Ability from LLMs to MLLMs


Distill n' Explain: explaining graph neural networks using simple surrogates


Distill on the Go: Online knowledge distillation in self-supervised learning


Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning


Distill the Image to Nowhere: Inversion Knowledge Distillation for Multimodal Machine Translation


Distill-C: Enhanced NL2SQL via Distilled Customization with LLMs


DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation


DistillCSE: Distilled Contrastive Learning for Sentence Embeddings


DistillSeq: A Framework for Safety Alignment Testing in Large Language Models using Knowledge Distillation


Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and Distillation


Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning


Distillation Improves Visual Place Recognition for Low Quality Images


Distillation Learning Guided by Image Reconstruction for One-Shot Medical Image Segmentation


Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model


Distillation Quantification for Large Language Models


Distillation and Refinement of Reasoning in Small Language Models for Document Re-ranking


Distillation of Discrete Diffusion through Dimensional Correlations


Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes (Technical Report)


Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great Again


Distillation-Free One-Step Diffusion for Real-World Image Super-Resolution


Distillation-Resistant Watermarking for Model Protection in NLP


Distillation-based fabric anomaly detection


Distilled Circuits: A Mechanistic Study of Internal Restructuring in Knowledge Distillation


Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching


Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation


Distilled GPT for Source Code Summarization


Distilled Lifelong Self-Adaptation for Configurable Systems


Distilled Neural Networks for Efficient Learning to Rank


Distilled Non-Semantic Speech Embeddings with Binary Neural Networks for Low-Resource Devices


Distilled Pooling Transformer Encoder for Efficient Realistic Image Dehazing


Distilled Pruning: Using Synthetic Data to Win the Lottery


Distilled Replay: Overcoming Forgetting through Synthetic Samples


Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective


Distilled Semantics for Comprehensive Scene Understanding from Videos


Distilling Audio-Visual Knowledge by Compositional Contrastive Learning


Distilling Autoregressive Models to Obtain High-Performance Non-Autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed


Distilling BlackBox to Interpretable models for Efficient Transfer Learning


Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition


Distilling Causal Effect of Data in Class-Incremental Learning


Distilling ChatGPT for Explainable Automated Student Answer Assessment


Distilling Coarse-to-Fine Semantic Matching Knowledge for Weakly Supervised 3D Visual Grounding


Distilling Cognitive Backdoor Patterns within an Image


Distilling Diffusion Models to Efficient 3D LiDAR Scene Completion


Distilling Effective Supervision from Severe Label Noise


Distilling Fine-grained Sentiment Understanding from Large Language Models


Distilling Governing Laws and Source Input for Dynamical Systems from Videos


Distilling Holistic Knowledge with Graph Neural Networks


Distilling Image Classifiers in Object Detectors


Distilling Implicit Multimodal Knowledge into Large Language Models for Zero-Resource Dialogue Generation


Distilling Importance Sampling for Likelihood Free Inference


Distilling Influences to Mitigate Prediction Churn in Graph Neural Networks


Distilling Interpretable Models into Human-Readable Code


Distilling Knowledge for Designing Computational Imaging Systems


Distilling Knowledge for Search-based Structured Prediction


Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition


Distilling Knowledge from Graph Convolutional Networks


Distilling Knowledge from Refinement in Multiple Instance Detection Networks


Distilling Knowledge from Self-Supervised Teacher by Embedding Graph Alignment


Distilling LLM Agent into Small Models with Retrieval and Code Tools


Distilling LLMs' Decomposition Abilities into Compact Language Models


Distilling Large Language Models using Skill-Occupation Graph Context for HR-Related Tasks


Distilling Large Vision-Language Model with Out-of-Distribution Generalizability


Distilling Local Texture Features for Colorectal Tissue Classification in Low Data Regimes


Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications


Distilling Model Failures as Directions in Latent Space


Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control


Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation


Distilling Object Detectors With Global Knowledge


Distilling Object Detectors via Decoupled Features


Distilling Object Detectors with Feature Richness


Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models


Distilling Reasoning Capabilities into Smaller Language Models


Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning


Distilling Reinforcement Learning Tricks for Video Games


Distilling Representations from GAN Generator via Squeeze and Span


Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck


Distilling Rule-based Knowledge into Large Language Models


Distilling Script Knowledge from Large Language Models for Constrained Language Planning


Distilling Semantic Concept Embeddings from Contrastively Fine-Tuned Language Models


Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes


Distilling Stereo Networks for Performant and Efficient Leaner Networks


Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping


Distilling Textual Priors from LLM to Efficient Image Fusion


Distilling Translations with Visual Awareness


Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data


Distilling Visual Priors from Self-Supervised Learning


Distilling a Powerful Student Model via Online Knowledge Distillation


Distilling a Pretrained Language Model to a Multilingual ASR Model


Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser


Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections


Distilling from Similar Tasks for Transfer Learning on a Budget


Distilling the Knowledge from Conditional Normalizing Flows


Distilling the Knowledge of BERT for Sequence-to-Sequence ASR


Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation


Distilling the Knowledge of Romanian BERTs Using Multiple Teachers


Distilling the Real Cost of Production Garbage Collectors


Distilling the Undistillable: Learning from a Nasty Teacher


Distilling the Unknown to Unveil Certainty


Distinct patterns of syntactic agreement errors in recurrent networks and humans


Distinctive Image Captioning: Leveraging Ground Truth Captions in CLIP Guided Reinforcement Learning


Distinguish Confusing Law Articles for Legal Judgment Prediction


Distinguish Confusion in Legal Judgment Prediction via Revised Relation Knowledge


Distinguishability Calibration to In-Context Learning


Distinguished In Uniform: Self Attention Vs. Virtual Nodes


Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network


Distinguishing Cause from Effect with Causal Velocity Models


Distinguishing Cell Phenotype Using Cell Epigenotype


Distinguishing Commercial from Editorial Content in News


Distinguishing Coupled Dark Energy Models with Neural Networks


Distinguishing Dirac and Majorana Heavy Neutrinos at Lepton Colliders


Distinguishing Fictional Voices: a Study of Authorship Verification Models for Quotation Attribution


Distinguishing Learning Rules with Brain Machine Interfaces


Distinguishing Level-2 Phylogenetic Networks Using Phylogenetic Invariants


Distinguishing Look-Alike Innocent and Vulnerable Code by Subtle Semantic Representation Learning and Explanation


Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNet


Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model


Distinguishing Orbiting and Infalling Dark Matter Particles with Machine Learning


Distinguishing binary black hole precessional morphologies with gravitational wave observations


Distinguishing correlation from causation using genome-wide association studies


Distinguishing differential susceptibility, diathesis-stress and vantage sensitivity: beyond the single gene and environment model


Distinguishing exoplanet companions from field stars in direct imaging using Gaia astrometry


Distinguishing immunological and behavioral effects of vaccination


Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes


Distinguishing rule- and exemplar-based generalization in learning systems


Distinguishing the sources of dielectron anisotropic flow at low beam energies


Distorting Embedding Space for Safety: A Defense Mechanism for Adversarially Robust Diffusion Models


Distortion Resilience for Goal-Oriented Semantic Communication


Distortion-Corrected Image Reconstruction with Deep Learning on an MRI-Linac


Distortion-aware Transformer in 360° Salient Object Detection


Distract Large Language Models for Automatic Jailbreak Attack


Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition


Distracting Downpour: Adversarial Weather Attacks for Motion Estimation


Distraction by auditory novelty during reading: Evidence for disruption in saccade planning, but not saccade execution


Distraction-Based Neural Networks for Document Summarization


Distractor generation for multiple-choice questions with predictive prompting and large language models


Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy


Distractor-free Generalizable 3D Gaussian Splatting


Distractors-Immune Representation Learning with Cross-modal Contrastive Regularization for Change Captioning


DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution


DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models


Distributed $k$-Clustering for Data with Heavy Noise


Distributed ARIMA Models for Ultra-long Time Series


Distributed Adaptive Norm Estimation for Blind System Identification in Wireless Sensor Networks


Distributed Adversarial Training to Robustify Deep Neural Networks at Scale


Distributed Associative Memory Network with Memory Refreshing Loss


Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses


Distributed Behavior Trees for Heterogeneous Robot Teams


Distributed Black-box Attack: Do Not Overestimate Black-box Attacks


Distributed Block-diagonal Approximation Methods for Regularized Empirical Risk Minimization


Distributed Bootstrap for Simultaneous Inference Under High Dimensionality


Distributed Certifiably Correct Range-Aided SLAM


Distributed Change Detection in Streaming Graph Signals


Distributed Charge Models of Liquid Methane and Ethane for Dielectric Effects and Solvation


Distributed Charging Coordination of Electric Trucks with Limited Charging Resources


Distributed Clustering for Multiuser Networks through Coalition Formation


Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning


Distributed Community Detection for Large Scale Networks Using Stochastic Block Model


Distributed Computing From First Principles


Distributed Conformal Prediction via Message Passing


Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks


Distributed Control of Descriptor Networks: A Convex Procedure for Augmented Sparsity


Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning


Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals


Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers


Distributed Deep Joint Source-Channel Coding over a Multiple Access Channel


Distributed Deep Joint Source-Channel Coding with Decoder-Only Side Information


Distributed Deep Learning in Open Collaborations


Distributed Discrete Morse Sandwich: Efficient Computation of Persistence Diagrams for Massive Scalar Data


Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles


Distributed Experimental Design Networks


Distributed Extra-gradient with Optimal Complexity and Communication Guarantees


Distributed Function Minimization in Apache Spark


Distributed Generalized Linear Models: A Privacy-Preserving Approach


Distributed Genetic Algorithm for Feature Selection


Distributed Graph Augmentation Protocols to Achieve Strong Connectivity in Multi-Agent Networks


Distributed Graph Embedding with Information-Oriented Random Walks


Distributed Heuristic Multi-Agent Path Finding with Communication


Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery


Distributed Inference over Linear Models using Alternating Gaussian Belief Propagation


Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems


Distributed Intelligent Video Surveillance for Early Armed Robbery Detection based on Deep Learning


Distributed Key Generation with Smart Contracts using zk-SNARKs


Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions


Distributed Lag Interaction Model with Index Modification


Distributed Learning of Finite Gaussian Mixtures


Distributed Learning of Mixtures of Experts


Distributed Learning over Networks with Graph-Attention-Based Personalization


Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks


Distributed Lyapunov Functions for Nonlinear Networks


Distributed MCMC inference for Bayesian Non-Parametric Latent Block Model


Distributed Majorization-Minimization for Laplacian Regularized Problems


Distributed Many-to-Many Protein Sequence Alignment using Sparse Matrices


Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers


Distributed Mixture-of-Agents for Edge Inference with Large Language Models


Distributed Model Predictive Control for Dynamic Cooperation of Multi-Agent Systems


Distributed Model Predictive Control for Heterogeneous Platoons with Affine Spacing Policies and Arbitrary Communication Topologies


Distributed Model Predictive Control for Piecewise Affine Systems Based on Switching ADMM


Distributed Momentum for Byzantine-resilient Learning


Distributed Monitoring for Data Distribution Shifts in Edge-ML Fraud Detection


Distributed Multi-agent Video Fast-forwarding


Distributed Multi-object Tracking under Limited Field of View Sensors


Distributed Multi-writer Multi-reader Atomic Register with Optimistically Fast Read and Write


Distributed Multivariate Regression Modeling For Selecting Biomarkers Under Data Protection Constraints


Distributed Nash Equilibrium Seeking in Coalition Games for Uncertain Euler-Lagrange Systems With Application to USV Swarm Confrontation


Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability


Distributed Online Planning for Min-Max Problems in Networked Markov Games


Distributed Online Rollout for Multivehicle Routing in Unmapped Environments


Distributed Optimal Control of Graph Symmetric Systems via Graph Filters


Distributed Optimization of Average Consensus Containment with Multiple Stationary Leaders


Distributed Optimization of Multi-Class SVMs


Distributed Optimization with Arbitrary Local Solvers


Distributed Optimization, Averaging via ADMM, and Network Topology


Distributed Out-of-Memory NMF on CPU/GPU Architectures


Distributed Planning for Rigid Robot Formations with Probabilistic Collision Avoidance


Distributed Pose-graph Optimization with Multi-level Partitioning for Collaborative SLAM


Distributed Power Flow and Distributed Optimization -- Formulation, Solution, and Open Source Implementation


Distributed Primal Outer Approximation Algorithm for Sparse Convex Programming with Separable Structures


Distributed Principal Component Analysis with Limited Communication


Distributed Quantum Circuit Cutting for Hybrid Quantum-Classical High-Performance Computing


Distributed Quantum Neural Networks on Distributed Photonic Quantum Computing


Distributed Quantum Neural Networks via Partitioned Features Encoding


Distributed Reconstruction from Compressive Measurements: Nonconvexity and Heterogeneity


Distributed Representations of Atoms and Materials for Machine Learning


Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V Communication


Distributed Robust Set-Invariance for Interconnected Linear Systems


Distributed Saddle-Point Problems Under Similarity


Distributed Scheduling of Quantum Circuits with Noise and Time Optimization


Distributed Semi-supervised Fuzzy Regression with Interpolation Consistency Regularization


Distributed Simulation and Visualization of The ALICE Detector Magnetic Field


Distributed Simulation of Statevectors and Density Matrices


Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge Distillation


Distributed Sparse Multicategory Discriminant Analysis


Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference


Distributed Subgraph Enumeration via Backtracking-based Framework


Distributed Thompson sampling under constrained communication


Distributed Time-Varying Gaussian Regression via Kalman Filtering


Distributed Timed Elastic Band (DTEB) Planner: Trajectory Sharing and Collision Prediction for Multi-Robot Systems


Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement Learning


Distributed Two-tier DRL Framework for Cell-Free Network: Association, Beamforming and Power Allocation


Distributed Variational Inference for Online Supervised Learning


Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models


Distributed Weighted Least Squares Estimator Based on ADMM


Distributed and Secure Kernel-Based Quantum Machine Learning


Distributed and Secure ML with Self-tallying Multi-party Aggregation


Distributed and parallel sparse convex optimization for radio interferometry with PURIFY


Distributed bundle adjustment with block-based sparse matrix compression for super large scale datasets


Distributed data-driven predictive control for cooperatively smoothing mixed traffic flow


Distributed deep learning on edge-devices: feasibility via adaptive compression


Distributed deep reinforcement learning for simulation control


Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence


Distributed formation-enforcing control for UAVs robust to observation noise in relative pose measurements


Distributed genetic algorithm for application placement in the compute continuum leveraging infrastructure nodes for optimization


Distributed linear regression by averaging


Distributed memory parallel adaptive tensor-train cross approximation


Distributed multi-agent Gaussian regression via finite-dimensional approximations


Distributed non-disclosive validation of predictive models by a modified ROC-GLM


Distributed nonconvex optimization for control of water networks with time-coupling constraints


Distributed optimization for nonrigid nano-tomography


Distributed photovoltaics provides key benefits for a highly renewable European energy system


Distributed quantum sensing in a continuous variable entangled network


Distributed representations of graphs for drug pair scoring


Distributed sampling, quantum communication witnesses, and measurement incompatibility


Distributed stochastic inertial-accelerated methods with delayed derivatives for nonconvex problems


Distributed-Memory DMRG via Sparse and Dense Parallel Tensor Contractions


Distributed-Memory Parallel Algorithms for Sparse Matrix and Sparse Tall-and-Skinny Matrix Multiplication


Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition


Distributed-Memory Sparse Kernels for Machine Learning


Distributed-Order Fractional Graph Operating Network


Distributed-memory $\mathcal{H}$-matrix Algebra I: Data Distribution and Matrix-vector Multiplication


DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia


Distributing Collaborative Multi-Robot Planning with Gaussian Belief Propagation


Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation


Distribution Aligned Diffusion and Prototype-guided network for Unsupervised Domain Adaptive Segmentation


Distribution Aligned Semantics Adaption for Lifelong Person Re-Identification


Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning


Distribution Alignment for Fully Test-Time Adaptation with Dynamic Online Data Streams


Distribution Alignment: A Unified Framework for Long-tail Visual Recognition


Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation


Distribution Calibration for Out-of-Domain Detection with Bayesian Approximation


Distribution Discrepancy and Feature Heterogeneity for Active 3D Object Detection


Distribution Free Prediction Sets for Node Classification


Distribution Grids May Be a Barrier To Residential Electrification


Distribution Guided Active Feature Acquisition


Distribution Knowledge Embedding for Graph Pooling


Distribution Matching Losses Can Hallucinate Features in Medical Image Translation


Distribution Matching for Crowd Counting


Distribution Matching for Rationalization


Distribution Matching for Self-Supervised Transfer Learning


Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling


Distribution Regression in Duration Analysis: an Application to Unemployment Spells


Distribution Regression with Sliced Wasserstein Kernels


Distribution Shift Inversion for Out-of-Distribution Prediction


Distribution Shifts at Scale: Out-of-distribution Detection in Earth Observation


Distribution free MMD tests for model selection with estimated parameters


Distribution inference risks: Identifying and mitigating sources of leakage


Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards


Distribution of Si II $λ$6355 Velocities of Type Ia Supernovae and Implications for Asymmetric Explosions


Distribution of points on the real line under a class of repulsive potentials


Distribution of the order parameter in strongly disordered superconductors: An analytic theory


Distribution-Aware Binarization of Neural Networks for Sketch Recognition


Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes


Distribution-Aware Continual Test-Time Adaptation for Semantic Segmentation


Distribution-Aware Data Expansion with Diffusion Models


Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System


Distribution-Aware Robust Learning from Long-Tailed Data with Noisy Labels


Distribution-Aware Testing of Neural Networks Using Generative Models


Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets


Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution Networks


Distribution-Free Calibration of Statistical Confidence Sets


Distribution-Free Conditional Median Inference


Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes


Distribution-Free Prediction Sets for Two-Layer Hierarchical Models


Distribution-Free Predictive Inference under Unknown Temporal Drift


Distribution-Free, Risk-Controlling Prediction Sets


Distribution-Informed Adaptation for kNN Graph Construction


Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective


Distribution-aware Fairness Test Generation


Distribution-aware Forgetting Compensation for Exemplar-Free Lifelong Person Re-identification


Distribution-aware Interactive Attention Network and Large-scale Cloud Recognition Benchmark on FY-4A Satellite Image


Distribution-aware Noisy-label Crack Segmentation


Distribution-based Emotion Recognition in Conversation


Distribution-based Sketching of Single-Cell Samples


Distribution-free and Model-free Multivariate Feature Screening via Multivariate Rank Distance Correlation


Distribution-free inference with hierarchical data


Distribution-free uncertainty quantification for inverse problems: application to weak lensing mass mapping


Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning


Distribution-informed and wavelength-flexible data-driven photoacoustic oximetry


Distributional Adaptive Soft Regression Trees


Distributional Bellman Operators over Mean Embeddings


Distributional Correlation--Aware Knowledge Distillation for Stock Trading Volume Prediction


Distributional Data Augmentation Methods for Low Resource Language


Distributional Depth-Based Estimation of Object Articulation Models


Distributional Discrepancy: A Metric for Unconditional Text Generation


Distributional GFlowNets with Quantile Flows


Distributional Gradient Boosting Machines


Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models


Distributional Individual Fairness in Clustering


Distributional Instrumental Variable Method


Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation


Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP Methods


Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning


Distributional Modeling for Location-Aware Adversarial Patches


Distributional Multi-Objective Decision Making


Distributional Off-Policy Evaluation for Slate Recommendations


Distributional Off-policy Evaluation with Bellman Residual Minimization


Distributional Offline Policy Evaluation with Predictive Error Guarantees


Distributional Probabilistic Model Checking


Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts


Distributional Reinforcement Learning based Integrated Decision Making and Control for Autonomous Surface Vehicles


Distributional Reinforcement Learning for Multi-Dimensional Reward Functions


Distributional Reinforcement Learning via Moment Matching


Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks


Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning


Distributional Shift Adaptation using Domain-Specific Features


Distributional Sliced-Wasserstein and Applications to Generative Modeling


Distributional Soft Actor-Critic with Three Refinements


Distributional constrained reinforcement learning for supply chain optimization


Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation


Distributional robustness of K-class estimators and the PULSE


Distributionally Ambiguous Optimization Techniques for Batch Bayesian Optimization


Distributionally Generative Augmentation for Fair Facial Attribute Classification


Distributionally Robust CVaR-Based Safety Filtering for Motion Planning in Uncertain Environments


Distributionally Robust Classifiers in Sentiment Analysis


Distributionally Robust Contract Theory for Edge AIGC Services in Teleoperation


Distributionally Robust Covariance Steering with Optimal Risk Allocation


Distributionally Robust Decision Making Leveraging Conditional Distributions


Distributionally Robust Differential Dynamic Programming with Wasserstein Distance


Distributionally Robust End-to-End Portfolio Construction


Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model


Distributionally Robust Graph-based Recommendation System


Distributionally Robust Language Modeling


Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation


Distributionally Robust Losses for Latent Covariate Mixtures


Distributionally Robust Lyapunov Function Search Under Uncertainty


Distributionally Robust Multilingual Machine Translation


Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization


Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation


Distributionally Robust Optimization with Markovian Data


Distributionally Robust Optimization with Probabilistic Group


Distributionally Robust Parametric Maximum Likelihood Estimation


Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits


Distributionally Robust Policy and Lyapunov-Certificate Learning


Distributionally Robust Post-hoc Classifiers under Prior Shifts


Distributionally Robust Predictive Runtime Verification under Spatio-Temporal Logic Specifications


Distributionally Robust Receive Combining


Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics


Distributionally robust Kalman filtering with volatility uncertainty


Distributionally robust risk evaluation with an isotonic constraint


Distributionally robust self-supervised learning for tabular data


Distributionally robust stochastic programs with side information based on trimmings -- Extended version


District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images


DistrictNet: Decision-aware learning for geographical districting


Disttack: Graph Adversarial Attacks Toward Distributed GNN Training


Disturbance Observer-based Robust Integral Control Barrier Functions for Nonlinear Systems with High Relative Degree


Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children


Ditch the Denoiser: Emergence of Noise Robustness in Self-Supervised Learning from Data Curriculum


Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System


Ditto: Fair and Robust Federated Learning Through Personalization


Ditto: Motion-Space Diffusion for Controllable Realtime Talking Head Synthesis


DiuSST: A conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive SST


DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization


DivClust: Controlling Diversity in Deep Clustering


DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages


DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization


DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models


DivScene: Benchmarking LVLMs for Object Navigation with Diverse Scenes and Objects


DivShift: Exploring Domain-Specific Distribution Shifts in Large-Scale, Volunteer-Collected Biodiversity Datasets


DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy


DivaTrack: Diverse Bodies and Motions from Acceleration-Enhanced Three-Point Trackers


Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition


Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry


Dive into the Chasm: Probing the Gap between In- and Cross-Topic Generalization


Dive into the Resolution Augmentations and Metrics in Low Resolution Face Recognition: A Plain yet Effective New Baseline


DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints


Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals


Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification


Divergence, thickness and hypergraph index for general Coxeter groups


Divergence-free tangential finite element methods for incompressible flows on surfaces


Divergences between Language Models and Human Brains


Divergent Ensemble Networks: Enhancing Uncertainty Estimation with Shared Representations and Independent Branching


DivergentNets: Medical Image Segmentation by Network Ensemble


Diverging network architecture of the $\textit{C. elegans}$ connectome and signaling network


Diverse 3D Hand Gesture Prediction from Body Dynamics by Bilateral Hand Disentanglement


Diverse Adversaries for Mitigating Bias in Training


Diverse Carbonates in Exoplanet Oceans Promote the Carbon Cycle


Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes


Diverse Controllable Diffusion Policy with Signal Temporal Logic


Diverse Cotraining Makes Strong Semi-Supervised Segmentor


Diverse Dance Synthesis via Keyframes with Transformer Controllers


Diverse Demonstrations Improve In-context Compositional Generalization


Diverse Embedding Expansion Network and Low-Light Cross-Modality Benchmark for Visible-Infrared Person Re-identification


Diverse Explanations From Data-Driven and Domain-Driven Perspectives in the Physical Sciences


Diverse Few-Shot Text Classification with Multiple Metrics


Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration


Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks


Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors


Diverse Image Captioning with Context-Object Split Latent Spaces


Diverse Image Captioning with Grounded Style


Diverse Image Generation via Self-Conditioned GANs


Diverse Image Generation with Diffusion Models and Cross Class Label Learning for Polyp Classification


Diverse In-Context Example Selection After Decomposing Programs and Aligned Utterances Improves Semantic Parsing


Diverse Keyphrase Generation with Neural Unlikelihood Training


Diverse Part Synthesis for 3D Shape Creation


Diverse Plausible 360-Degree Image Outpainting for Efficient 3DCG Background Creation


Diverse Plausible Shape Completions from Ambiguous Depth Images


Diverse Policies Converge in Reward-free Markov Decision Processe


Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations


Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints


Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift


Diverse Rare Sample Generation with Pretrained GANs


Diverse Representation Embedding for Lifelong Person Re-Identification


Diverse Retrieval-Augmented In-Context Learning for Dialogue State Tracking


Diverse Reviewer Suggestion for Extending Conference Program Committees


Diverse Sample Generation: Pushing the Limit of Generative Data-free Quantization


Diverse Semantic Image Editing with Style Codes


Diverse Semantic Image Synthesis via Probability Distribution Modeling


Diverse Teacher-Students for Deep Safe Semi-Supervised Learning under Class Mismatch


Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video Classification


Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors


Diverse Title Generation for Stack Overflow Posts with Multiple Sampling Enhanced Transformer


Diverse Video Captioning by Adaptive Spatio-temporal Attention


Diverse Video Generation using a Gaussian Process Trigger


Diverse Weight Averaging for Out-of-Distribution Generalization


Diverse and Aligned Audio-to-Video Generation via Text-to-Video Model Adaptation


Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference


Diverse and Specific Clarification Question Generation with Keywords


Diverse and Styled Image Captioning Using SVD-Based Mixture of Recurrent Experts


Diverse communities behave like typical random ecosystems


Diverse feature visualizations reveal invariances in early layers of deep neural networks


Diverse polarization angle swings from a repeating fast radio burst source


Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation


Diverse, Difficult, and Odd Instances (D2O): A New Test Set for Object Classification


DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection


Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation


Diversification in Session-based News Recommender Systems


Diversified Adversarial Attacks based on Conjugate Gradient Method


Diversified Batch Selection for Training Acceleration


Diversified and Personalized Multi-rater Medical Image Segmentation


Diversified in-domain synthesis with efficient fine-tuning for few-shot classification


Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets


Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation


Diversify and Conquer: Diversity-Centric Data Selection with Iterative Refinement


Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers


Diversify and Disambiguate: Learning From Underspecified Data


Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQA


Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts


Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy


Diversifying Dialog Generation via Adaptive Label Smoothing


Diversifying Dialogue Generation with Non-Conversational Text


Diversifying Message Aggregation in Multi-Agent Communication via Normalized Tensor Nuclear Norm Regularization


Diversifying Query: Region-Guided Transformer for Temporal Sentence Grounding


Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEs


Diversifying Task-oriented Dialogue Response Generation with Prototype Guided Paraphrasing


Diversifying the High-level Features for better Adversarial Transferability


Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration


Diversity Aware Relevance Learning for Argument Search


Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization


Diversity Enhanced Active Learning with Strictly Proper Scoring Rules


Diversity Enhanced Narrative Question Generation for Storybooks


Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation


Diversity Measures: Domain-Independent Proxies for Failure in Language Model Queries


Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning


Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining Datasets


Diversity Transfer Network for Few-Shot Learning


Diversity and Generalization in Neural Network Ensembles


Diversity dilemmas: uncovering gender and nationality biases in graduate admissions across top North American computer science programs


Diversity enables the jump towards cooperation for the Traveler's Dilemma


Diversity in Fashion Recommendation using Semantic Parsing


Diversity in Valuing Social Contact and Risk Tolerance Lead to the Emergence of Homophily in Populations Facing Infectious Threats


Diversity in deep generative models and generative AI


Diversity inducing Information Bottleneck in Model Ensembles


Diversity matters: Robustness of bias measurements in Wikidata


Diversity of Artists in Major U.S. Museums


Diversity of emergent dynamics in competitive threshold-linear networks


Diversity of symptom phenotypes in SARS-CoV-2 community infections observed in multiple large datasets


Diversity patterns and speciation processes in a two-island system with continuous migration


Diversity vs. Recognizability: Human-like generalization in one-shot generative models


Diversity, Agreement, and Polarization in Elections


Diversity-Aware Batch Active Learning for Dependency Parsing


Diversity-Aware Coherence Loss for Improving Neural Topic Models


Diversity-Aware Weighted Majority Vote Classifier for Imbalanced Data


Diversity-Based Generalization for Unsupervised Text Classification under Domain Shift


Diversity-Driven Extensible Hierarchical Reinforcement Learning


Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment


Diversity-Driven View Subset Selection for Indoor Novel View Synthesis


Diversity-Guided MLP Reduction for Efficient Large Vision Transformers


Diversity-aware Channel Pruning for StyleGAN Compression


Diversity-based Deep Reinforcement Learning Towards Multidimensional Difficulty for Fighting Game AI


Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay


Divertor shaping with neutral baffling as a solution to the tokamak power exhaust challenge


DiviK: Divisive intelligent K-Means for hands-free unsupervised clustering in big biological data


Divide & Bind Your Attention for Improved Generative Semantic Nursing


Divide (Text) and Conquer (Sentiment): Improved Sentiment Classification by Constituent Conflict Resolution


Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions


Divide and Conquer in Video Anomaly Detection: A Comprehensive Review and New Approach


Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization


Divide and Conquer: An Ensemble Approach for Hostile Post Detection in Hindi


Divide and Conquer: Answering Questions with Object Factorization and Compositional Reasoning


Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement Learning


Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model


Divide and Conquer: Hybrid Pre-training for Person Search


Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents


Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning


Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models


Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning


Divide and conquer methods for functions of matrices with banded or hierarchical low-rank structure


Divide and not forget: Ensemble of selectively trained experts in Continual Learning


Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors


Divide, Conquer and Combine: A Training-Free Framework for High-Resolution Image Perception in Multimodal Large Language Models


Divide, Reweight, and Conquer: A Logit Arithmetic Approach for In-Context Learning


Divide-and-Conquer Determinization of Büchi Automata based on SCC Decomposition


Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors


Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer


Divide-and-conquer with finite sample sizes: valid and efficient possibilistic inference


Divide-or-Conquer? Which Part Should You Distill Your LLM?


DivideMix: Learning with Noisy Labels as Semi-supervised Learning


Divided by discipline? A systematic literature review on the quantification of online sexism and misogyny using a semi-automated approach


Divider: Delay-Time Based Sender Identification in Automotive Networks


Diving Deep into Modes of Fact Hallucinations in Dialogue Systems


Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction


Diving Deep into the Motion Representation of Video-Text Models


Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset


Diving into the Fusion of Monocular Priors for Generalized Stereo Matching


Diving with Penguins: Detecting Penguins and their Prey in Animal-borne Underwater Videos via Deep Learning


Divisi: Interactive Search and Visualization for Scalable Exploratory Subgroup Analysis


Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation


DmifNet:3D Shape Reconstruction Based on Dynamic Multi-Branch Information Fusion