Rescue Implicit and Long-tail Cases: Nearest Neighbor Relation Extraction


Rescue: Ranking LLM Responses with Partial Ordering to Improve Response Generation


RescueNet: A High Resolution UAV Semantic Segmentation Benchmark Dataset for Natural Disaster Damage Assessment


Rescuing neural spike train models from bad MLE


Research Artifacts in Software Engineering Publications: Status and Trends


Research Explosion: More Effort to Climb onto Shoulders of the Giant


Research Reproducibility as a Survival Analysis


Research Trends and Applications of Data Augmentation Algorithms


Research impact evaluation based on effective authorship contribution sensitivity: h-leadership index


Research on Event Accumulator Settings for Event-Based SLAM


Research on Robot Path Planning Based on Reinforcement Learning


ResearchTown: Simulator of Human Research Community


Researching Alignment Research: Unsupervised Analysis


Resemblance of the power-law scaling behavior of a non-Markovian and nonlinear point processes


Reserve Provision from Electric Vehicles: Aggregate Boundaries and Stochastic Model Predictive Control


Reservoir Computing Using Non-Uniform Binary Cellular Automata


Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data


Reservoir Computing meets Recurrent Kernels and Structured Transforms


Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems


Reservoir History Matching of the Norne field with generative exotic priors and a coupled Mixture of Experts -- Physics Informed Neural Operator Forward Model


Reservoir Memory Machines as Neural Computers


Reservoir-enhanced Segment Anything Model for Subsurface Diagnosis


Reset-Free Lifelong Learning with Skill-Space Planning


Reset-free Trial-and-Error Learning for Robot Damage Recovery


Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual Noise


Reshape Dimensions Network for Speaker Recognition


ReshapeIT: Reliable Shape Interaction with Implicit Template for Anatomical Structure Reconstruction


Reshaping Free-Text Radiology Notes Into Structured Reports With Generative Transformers


Reshaping the Online Data Buffering and Organizing Mechanism for Continual Test-Time Adaptation


ResiDual: Transformer with Dual Residual Connections


Residual Deep Gaussian Processes on Manifolds


Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imaging


Residual Dense Swin Transformer for Continuous Depth-Independent Ultrasound Imaging


Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation


Residual Enhanced Multi-Hypergraph Neural Network


Residual Features and Unified Prediction Network for Single Stage Detection


Residual Finiteness of $A_{2,3,2n}$ Triangle Artin Groups


Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis


Residual Importance Weighted Transfer Learning For High-dimensional Linear Regression


Residual Kolmogorov-Arnold Network for Enhanced Deep Learning


Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning


Residual Local Feature Network for Efficient Super-Resolution


Residual Multi-Task Learner for Applied Ranking


Residual Neural Networks for the Prediction of Planetary Collision Outcomes


Residual Pathway Priors for Soft Equivariance Constraints


Residual Policy Learning for Shared Autonomy


Residual Policy Learning for Vehicle Control of Autonomous Racing Cars


Residual Pose: A Decoupled Approach for Depth-based 3D Human Pose Estimation


Residual Prior-driven Frequency-aware Network for Image Fusion


Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics


Residual Spatial Attention Network for Retinal Vessel Segmentation


Residual Stream Analysis with Multi-Layer SAEs


Residual Tensor Train: A Quantum-inspired Approach for Learning Multiple Multilinear Correlations


Residual neural networks to classify the high frequency emission in core-collapse supernova gravitational waves


Residual vector quantization for KV cache compression in large language model


Residual-based attention and connection to information bottleneck theory in PINNs


Residual2Vec: Debiasing graph embedding with random graphs


ResidualSketch: Enhancing Layer Efficiency and Error Reduction in Hierarchical Heavy Hitter Detection with ResNet Innovations


Residue-Based Natural Language Adversarial Attack Detection


Resilience assessment framework for cyber-physical distribution power system based on coordinated cyber-physical attacks under dynamic game


Resilience from Diversity: Population-based approach to harden models against adversarial attacks


Resilience in multiplex networks by addition of cross-repulsive links


Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks


Resilience of Entropy Model in Distributed Neural Networks


Resilience of Hund's rule in the Chemical Space of Small Organic Molecules


Resilience of the autocatalytic feedback loop for gene regulation


Resilience through Scene Context in Visual Referring Expression Generation


Resilient Consensus-based Multi-agent Reinforcement Learning with Function Approximation


Resilient Distributed Vector Consensus Using Centerpoints


Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage Normalization


Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis


Resilient Self-Debugging Software Protection


Resilient UAV Swarm Communications with Graph Convolutional Neural Network


Resilient and Adaptive Framework for Large Scale Android Malware Fingerprinting using Deep Learning and NLP Techniques


Resilient and Adaptive Replanning for Multi-Robot Target Tracking with Sensing and Communication Danger Zones


Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned


Resilient and consistent multirobot cooperative localization with covariance intersection


Resistance Against Manipulative AI: key factors and possible actions


Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation


Resistant Multiple Sparse Canonical Correlation


Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective


Resisting Deep Learning Models Against Adversarial Attack Transferability via Feature Randomization


Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree


Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model


ResoFilter: Fine-grained Synthetic Data Filtering for Large Language Models through Data-Parameter Resonance Analysis


Resolution Switchable Networks for Runtime Efficient Image Recognition


Resolution enhancement of placenta histological images using deep learning


Resolution enhancement, noise suppression, and joint T2* decay estimation in dual-echo sodium-23 MR imaging using anatomically-guided reconstruction


Resolution learning in deep convolutional networks using scale-space theory


Resolution of Simpson's paradox via the common cause principle


Resolution-Adaptive Micro-Doppler Spectrogram for Human Activity Recognition


Resolution-Invariant Image Classification based on Fourier Neural Operators


Resolvent-Type Data-Driven Learning of Generators for Unknown Continuous-Time Dynamical Systems


ResolverFuzz: Automated Discovery of DNS Resolver Vulnerabilities with Query-Response Fuzzing


Resolving 3D Human Pose Ambiguities with 3D Scene Constraints


Resolving Anomalies in the Behaviour of a Modularity Inducing Problem Domain with Distributional Fitness Evaluation


Resolving Camera Position for a Practical Application of Gaze Estimation on Edge Devices


Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs


Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization


Resolving Implicit Coordination in Multi-Agent Deep Reinforcement Learning with Deep Q-Networks & Game Theory


Resolving Indirect Referring Expressions for Entity Selection


Resolving Knowledge Conflicts in Large Language Models


Resolving Legalese: A Multilingual Exploration of Negation Scope Resolution in Legal Documents


Resolving Lexical Bias in Edit Scoping with Projector Editor Networks


Resolving Multi-Condition Confusion for Finetuning-Free Personalized Image Generation


Resolving New Keynesian Anomalies with Wealth in the Utility Function


Resolving Prime Modules: The Structure of Pseudo-cographs and Galled-Tree Explainable Graphs


Resolving References in Visually-Grounded Dialogue via Text Generation


Resolving References to Objects in Photographs using the Words-As-Classifiers Model


Resolving Semantic Confusions for Improved Zero-Shot Detection


Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning


Resolving conceptual issues in Modern Coexistence Theory


Resolving gas bubbles ascending in liquid metal from low-SNR neutron radiography images


Resolving label uncertainty with implicit posterior models


Resolving nonuniform temperature distributions with single-beam absorption spectroscopy. Part II: Implementation from broadband spectra


Resolving pseudosymmetry in tetragonal ZrO2 using EBSD with a modified dictionary indexing approach


Resolving social dilemmas with minimal reward transfer


Resolving the microscopic hydrodynamics at the moving contact line


Resonance Complexity Theory and the Architecture of Consciousness: A Field-Theoretic Model of Resonant Interference and Emergent Awareness


Resonance RoPE: Improving Context Length Generalization of Large Language Models


Resonant Cancellation Effect in Ramsey Experiments


Resonant Scanning Design and Control for Fast Spatial Sampling


Resonant contributions to polarized proton structure functions


Resonant top pair searches at the LHC: a window to electroweak phase transition


Resource Allocation for Twin Maintenance and Computing Task Processing in Digital Twin Vehicular Edge Computing Network


Resource Allocation for Vehicle Platooning in 5G NR-V2X via Deep Reinforcement Learning


Resource Allocation to Agents with Restrictions: Maximizing Likelihood with Minimum Compromise


Resource Aware Person Re-identification across Multiple Resolutions


Resource Constrained Model Compression via Minimax Optimization for Spiking Neural Networks


Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?


Resource Constrained Semantic Segmentation for Waste Sorting


Resource Efficient Boolean Function Solver on Quantum Computer


Resource Efficient Mountainous Skyline Extraction using Shallow Learning


Resource Efficient Perception for Vision Systems


Resource Leak Checker (RLC#) for C# Code using CodeQL


Resource Sharing Through Multi-Round Matchings


Resource Usage Analysis from a Different Perspective on MOOC Dropout


Resource allocation for text semantic communications


Resource analysis of quantum algorithms for coarse-grained protein folding models


Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systems


Resource-Aware Arabic LLM Creation: Model Adaptation, Integration, and Multi-Domain Testing


Resource-Efficient Affordance Grounding with Complementary Depth and Semantic Prompts


Resource-Efficient Invariant Networks: Exponential Gains by Unrolled Optimization


Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps


Resource-Interaction Graph: Efficient Graph Representation for Anomaly Detection


Resource-Limited Automated Ki67 Index Estimation in Breast Cancer


Resource-aware IoT Control: Saving Communication through Predictive Triggering


Resource-efficient Inference with Foundation Model Programs


Resource-efficient fault-tolerant one-way quantum repeater with code concatenation


Resource-efficient simulation of noisy quantum circuits and application to network-enabled QRAM optimization


Resources and Evaluations for Multi-Distribution Dense Information Retrieval


Resources and Few-shot Learners for In-context Learning in Slavic Languages


RespDiff: An End-to-End Multi-scale RNN Diffusion Model for Respiratory Waveform Estimation from PPG Signals


RespVAD: Voice Activity Detection via Video-Extracted Respiration Patterns


Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect


Respecting causality is all you need for training physics-informed neural networks


RespireNet: A Deep Neural Network for Accurately Detecting Abnormal Lung Sounds in Limited Data Setting


Response Enhanced Semi-supervised Dialogue Query Generation


Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks


Response Generation by Context-aware Prototype Editing


Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline


Response Selection with Topic Clues for Retrieval-based Chatbots


Response Surface Methodology coupled with desirability functions for multi-objective optimization: minimizing indoor overheating hours and maximizing useful daylight illuminance


Response Tuning: Aligning Large Language Models without Instruction


Response of Vertical Velocities in Extratropical Precipitation Extremes to Climate Change


Response to an external field of a generalized Langevin equation with stochastic resetting of the memory kernel


Responses of Unemployment to Productivity Changes for a General Matching Technology


Responsibility Perspective Transfer for Italian Femicide News


Responsible Diffusion Models via Constraining Text Embeddings within Safe Regions


Responsible Disclosure of Generative Models Using Scalable Fingerprinting


RestNet: Boosting Cross-Domain Few-Shot Segmentation with Residual Transformation Network


Restart Sampling for Improving Generative Processes


Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^{-7/4})$ Complexity


Restarts subject to approximate sharpness: A parameter-free and optimal scheme for first-order methods


Restats: A Test Coverage Tool for RESTful APIs


Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture


Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption


Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image Representations


Restoration of User Videos Shared on Social Media


Restoration of the Tully-Fisher Relation by Statistical Rectification


Restore Anything Model via Efficient Degradation Adaptation


Restore Anything Pipeline: Segment Anything Meets Image Restoration


Restore Anything with Masks: Leveraging Mask Image Modeling for Blind All-in-One Image Restoration


Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV


RestoreFormer++: Towards Real-World Blind Face Restoration from Undegraded Key-Value Pairs


RestoreFormer: High-Quality Blind Face Restoration from Undegraded Key-Value Pairs


Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance


RestorerID: Towards Tuning-Free Face Restoration with ID Preservation


Restoring Ancient Ideograph: A Multimodal Multitask Neural Network Approach


Restoring Connectivity in Vascular Segmentation using a Learned Post-Processing Model


Restoring Execution Environments of Jupyter Notebooks


Restoring Hebrew Diacritics Without a Dictionary


Restoring Images in Adverse Weather Conditions via Histogram Transformer


Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch Network


Restoring Negative Information in Few-Shot Object Detection


Restoring Real-World Degraded Events Improves Deblurring Quality


Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network


Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models


Restoring ancient text using deep learning: a case study on Greek epigraphy


Restoring balance: principled under/oversampling of data for optimal classification


Restoring cosmological concordance with early dark energy and massive neutrinos?


Restormer-Plus for Real World Image Deraining: One State-of-the-Art Solution to the GT-RAIN Challenge (CVPR 2023 UG2+ Track 3)


Restricted Bernoulli Matrix Factorization: Balancing the trade-off between prediction accuracy and coverage in classification based collaborative filtering


Restricted Boltzmann machine representation for the groundstate and excited states of Kitaev Honeycomb model


Restricted Path Characteristic Function Determines the Law of Stochastic Processes


Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders


Restricting to the chip architecture maintains the quantum neural network accuracy


Restructuring Batch Normalization to Accelerate CNN Training


Restructuring Conversations using Discourse Relations for Zero-shot Abstractive Dialogue Summarization


Restructuring Vector Quantization with the Rotation Trick


Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical Guarantees


Result Diversification in Search and Recommendation: A Survey


Results of a Single Blind Literary Taste Test with Short Anonymized Novel Fragments


Results of the Big ANN: NeurIPS'23 competition


ResumeAtlas: Revisiting Resume Classification with Large-Scale Datasets and Large Language Models


ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement


Resurrect3D: An Open and Customizable Platform for Visualizing and Analyzing Cultural Heritage Artifacts


Resurrecting Label Propagation for Graphs with Heterophily and Label Noise


Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning


RetFiner: A Vision-Language Refinement Scheme for Retinal Foundation Models


RetGen: A Joint framework for Retrieval and Grounded Text Generation Modeling


RetICL: Sequential Retrieval of In-Context Examples with Reinforcement Learning


RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation


Retail-786k: a Large-Scale Dataset for Visual Entity Matching


RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluation


Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs


Retention Time of Peptides in Liquid Chromatography Is Well Estimated upon Deep Transfer Learning


Retention of surface water on tidally locked rocky planets in the Venus zone around M dwarfs


Rethink DARTS Search Space and Renovate a New Benchmark


Rethink Predicting the Optical Flow with the Kinetics Perspective


Rethink Sparse Signals for Pose-guided Text-to-image Generation


Rethink about the Word-level Quality Estimation for Machine Translation from Human Judgement


Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs


Rethink the Role of Deep Learning towards Large-scale Quantum Systems


Rethinking 3D Dense Caption and Visual Grounding in A Unified Framework through Prompt-based Localization


Rethinking 3D LiDAR Point Cloud Segmentation


Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging cases


Rethinking Adam: A Twofold Exponential Moving Average Approach


Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding


Rethinking Alignment in Video Super-Resolution Transformers


Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation


Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning


Rethinking Architecture Selection in Differentiable NAS


Rethinking Assumptions in Deep Anomaly Detection


Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical Imaging


Rethinking Attention-Model Explainability through Faithfulness Violation Test


Rethinking Attribute Representation and Injection for Sentiment Classification


Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective


Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation


Rethinking Benchmark and Contamination for Language Models with Rephrased Samples


Rethinking Benchmarks for Cross-modal Image-text Retrieval


Rethinking Bias-Variance Trade-off for Generalization of Neural Networks


Rethinking Boundary Discontinuity Problem for Oriented Object Detection


Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective


Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective


Rethinking CLIP-based Video Learners in Cross-Domain Open-Vocabulary Action Recognition


Rethinking CNN Models for Audio Classification


Rethinking Cancer Gene Identification through Graph Anomaly Analysis


Rethinking Causal Relationships Learning in Graph Neural Networks


Rethinking Cell Counting Methods: Decoupling Counting and Localization


Rethinking Centered Kernel Alignment in Knowledge Distillation


Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models


Rethinking Chunk Size For Long-Document Retrieval: A Multi-Dataset Analysis


Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective


Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning Perspective


Rethinking Classification and Localization for Object Detection


Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning


Rethinking Code Refinement: Learning to Judge Code Efficiency


Rethinking Common Assumptions to Mitigate Racial Bias in Face Recognition Datasets


Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors


Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models


Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement


Rethinking Contrastive Learning in Session-based Recommendation


Rethinking Conversational Recommendations: Is Decision Tree All You Need?


Rethinking Cross-Domain Pedestrian Detection: A Background-Focused Distribution Alignment Framework for Instance-Free One-Stage Detectors


Rethinking Cross-Modal Interaction in Multimodal Diffusion Transformers


Rethinking Crowd-Sourced Evaluation of Neuron Explanations


Rethinking CyberSecEval: An LLM-Aided Approach to Evaluation Critique


Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach


Rethinking Data Augmentation for Robust Visual Question Answering


Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation


Rethinking Data Augmentation for Tabular Data in Deep Learning


Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks


Rethinking Data Perturbation and Model Stabilization for Semi-supervised Medical Image Segmentation


Rethinking Data Selection at Scale: Random Selection is Almost All You Need


Rethinking Data-Free Quantization as a Zero-Sum Game


Rethinking Decoder Design: Improving Biomarker Segmentation Using Depth-to-Space Restoration and Residual Linear Attention


Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective


Rethinking Deep Image Prior for Denoising


Rethinking Deep Learning: Non-backpropagation and Non-optimization Machine Learning Approach Using Hebbian Neural Networks


Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN


Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation


Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets


Rethinking Detection Based Table Structure Recognition for Visually Rich Document Images


Rethinking Differentiable Search for Mixed-Precision Neural Networks


Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution


Rethinking Diffusion Model in High Dimension


Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior


Rethinking Dilated Convolution for Real-time Semantic Segmentation


Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective


Rethinking Disparity: A Depth Range Free Multi-View Stereo Based on Disparity


Rethinking Diversified and Discriminative Proposal Generation for Visual Grounding


Rethinking Document-level Neural Machine Translation


Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment


Rethinking Domain Generalization: Discriminability and Generalizability


Rethinking Drone-Based Search and Rescue with Aerial Person Detection


Rethinking Early-Fusion Strategies for Improved Multispectral Object Detection


Rethinking Efficient Lane Detection via Curve Modeling


Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMamba


Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods


Rethinking End-to-End 2D to 3D Scene Segmentation in Gaussian Splatting


Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach


Rethinking Evaluation Methodology for Audio-to-Score Alignment


Rethinking Evaluation in ASR: Are Our Models Robust Enough?


Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words


Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching


Rethinking Exponential Averaging of the Fisher


Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning


Rethinking Eye-blink: Assessing Task Difficulty through Physiological Representation of Spontaneous Blinking


Rethinking FUN: Frequency-Domain Utilization Networks


Rethinking Fair Graph Neural Networks from Re-balancing


Rethinking Fano's Inequality in Ensemble Learning


Rethinking Features-Fused-Pyramid-Neck for Object Detection


Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark


Rethinking Few-shot Class-incremental Learning: Learning from Yourself


Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning


Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help?


Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate


Rethinking Generalizability and Discriminability of Self-Supervised Learning from Evolutionary Game Theory Perspective


Rethinking Generalization in Few-Shot Classification


Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study


Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL


Rethinking Gradient Operator for Exposing AI-enabled Face Forgeries


Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable Targets


Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering


Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective


Rethinking Graph Convolutional Networks in Knowledge Graph Completion


Rethinking Graph Masked Autoencoders through Alignment and Uniformity


Rethinking Graph Neural Architecture Search from Message-passing


Rethinking Graph Neural Networks for Anomaly Detection


Rethinking Graph Regularization for Graph Neural Networks


Rethinking Graph Transformers with Spectral Attention


Rethinking Guidance Information to Utilize Unlabeled Samples:A Label Encoding Perspective


Rethinking High-speed Image Reconstruction Framework with Spike Camera


Rethinking How to Evaluate Language Model Jailbreak


Rethinking Image Deraining via Rain Streaks and Vapors


Rethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clustering


Rethinking Image Super-Resolution from Training Data Perspectives


Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems


Rethinking Image-based Table Recognition Using Weakly Supervised Methods


Rethinking Importance Weighting for Deep Learning under Distribution Shift


Rethinking Independent Cross-Entropy Loss For Graph-Structured Data


Rethinking Inductive Biases for Surface Normal Estimation


Rethinking Interactive Image Segmentation: Feature Space Annotation


Rethinking Intermediate Layers design in Knowledge Distillation for Kidney and Liver Tumor Segmentation


Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment


Rethinking IoU-based Optimization for Single-stage 3D Object Detection


Rethinking Irregular Scene Text Recognition


Rethinking Kernel Methods for Node Representation Learning on Graphs


Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving


Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation


Rethinking Knowledge Graph Evaluation Under the Open-World Assumption


Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models


Rethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models


Rethinking Learnable Tree Filter for Generic Feature Transform


Rethinking Learning Approaches for Long-Term Action Anticipation


Rethinking Learning Rate Tuning in the Era of Large Language Models


Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline


Rethinking Legal Judgement Prediction in a Realistic Scenario in the Era of Large Language Models


Rethinking Link Prediction for Directed Graphs


Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective


Rethinking Local Perception in Lightweight Vision Transformer


Rethinking Localization Map: Towards Accurate Object Perception with Self-Enhancement Maps


Rethinking Loss Functions for Fact Verification


Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem


Rethinking Machine Unlearning in Image Generation Models


Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective


Rethinking Medical Report Generation: Disease Revealing Enhancement with Knowledge Graph


Rethinking Memory in AI: Taxonomy, Operations, Topics, and Future Directions


Rethinking Mesh Watermark: Towards Highly Robust and Adaptable Deep 3D Mesh Watermarking


Rethinking Minimal Sufficient Representation in Contrastive Learning


Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation


Rethinking Mitosis Detection: Towards Diverse Data and Feature Representation


Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity


Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation


Rethinking Momentum Knowledge Distillation in Online Continual Learning


Rethinking Motion Deblurring Training: A Segmentation-Based Method for Simulating Non-Uniform Motion Blurred Images


Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems


Rethinking Multi-view Representation Learning via Distilled Disentangling


Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You Need


Rethinking Natural Adversarial Examples for Classification Models


Rethinking Nearest Neighbors for Visual Classification


Rethinking Negative Instances for Generative Named Entity Recognition


Rethinking Negative Pairs in Code Search


Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework


Rethinking Neural Networks With Benford's Law


Rethinking Node-wise Propagation for Large-scale Graph Learning


Rethinking Noise Synthesis and Modeling in Raw Denoising


Rethinking Noisy Label Learning in Real-world Annotation Scenarios from the Noise-type Perspective


Rethinking Non-Negative Matrix Factorization with Implicit Neural Representations


Rethinking Normalization and Elimination Singularity in Neural Networks


Rethinking Object Detection in Retail Stores


Rethinking Object Saliency Ranking: A Novel Whole-flow Processing Paradigm


Rethinking Offensive Text Detection as a Multi-Hop Reasoning Problem


Rethinking Optical Flow from Geometric Matching Consistent Perspective


Rethinking Optimization and Architecture for Tiny Language Models


Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection


Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution


Rethinking Out-of-distribution (OOD) Detection: Masked Image Modeling is All You Need


Rethinking PGD Attack: Is Sign Function Necessary?


Rethinking PRL: A Multiscale Progressively Residual Learning Network for Inverse Halftoning


Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited


Rethinking Patch Dependence for Masked Autoencoders


Rethinking Performance Estimation in Neural Architecture Search


Rethinking Performance Gains in Image Dehazing Networks


Rethinking Perturbations in Encoder-Decoders for Fast Training


Rethinking Polyp Segmentation from an Out-of-Distribution Perspective


Rethinking Portrait Matting with Privacy Preserving


Rethinking Pre-Trained Feature Extractor Selection in Multiple Instance Learning for Whole Slide Image Classification


Rethinking Prior Information Generation with CLIP for Few-Shot Segmentation


Rethinking Prompt Optimizers: From Prompt Merits to Optimization


Rethinking Propagation for Unsupervised Graph Domain Adaptation


Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization


Rethinking Query-based Transformer for Continual Image Segmentation


Rethinking RAFT for Efficient Optical Flow


Rethinking RGB-Event Semantic Segmentation with a Novel Bidirectional Motion-enhanced Event Representation


Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning


Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection


Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy


Rethinking Recurrent Neural Networks and Other Improvements for Image Classification


Rethinking Repetition Problems of LLMs in Code Generation


Rethinking Resolution in the Context of Efficient Video Recognition


Rethinking Reward Model Evaluation Through the Lens of Reward Overoptimization


Rethinking Robust Contrastive Learning from the Adversarial Perspective


Rethinking Robustness in Machine Learning: A Posterior Agreement Approach


Rethinking Robustness of Model Attributions


Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation


Rethinking Rotation-Invariant Recognition of Fine-grained Shapes from the Perspective of Contour Points


Rethinking Round-Trip Translation for Machine Translation Evaluation


Rethinking Saliency-Guided Weakly-Supervised Semantic Segmentation


Rethinking Self-Supervised Learning: Small is Beautiful


Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective


Rethinking Self-training for Semi-supervised Landmark Detection: A Selection-free Approach


Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition


Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective


Rethinking Semi-supervised Learning with Language Models


Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting


Rethinking Sharpness-Aware Minimization as Variational Inference


Rethinking Skill Extraction in the Job Market Domain using Large Language Models


Rethinking Smart Contract Fuzzing: Fuzzing With Invocation Ordering and Important Branch Revisiting


Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective


Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator


Rethinking Software Misconfigurations in the Real World: An Empirical Study and Literature Analysis


Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation


Rethinking Spatial Invariance of Convolutional Networks for Object Counting


Rethinking Supervised Learning and Reinforcement Learning in Task-Oriented Dialogue Systems


Rethinking Surgical Instrument Segmentation: A Background Image Can Be All You Need


Rethinking Symmetric Matrix Factorization: A More General and Better Clustering Perspective


Rethinking Tabular Data Understanding with Large Language Models


Rethinking Targeted Adversarial Attacks For Neural Machine Translation


Rethinking Task Sampling for Few-shot Vision-Language Transfer Learning


Rethinking Temporal Fusion for Video-based Person Re-identification on Semantic and Time Aspect


Rethinking Temporal Fusion with a Unified Gradient Descent View for 3D Semantic Occupancy Prediction


Rethinking Text Attribute Transfer: A Lexical Analysis


Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach


Rethinking Text-based Protein Understanding: Retrieval or LLM?


Rethinking The Memory Staleness Problem In Dynamics GNN


Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation


Rethinking Time Encoding via Learnable Transformation Functions


Rethinking Token Reduction for State Space Models


Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules


Rethinking Training from Scratch for Object Detection


Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis


Rethinking Transformer-Based Blind-Spot Network for Self-Supervised Image Denoising


Rethinking Transformer-based Set Prediction for Object Detection


Rethinking Transformers in Solving POMDPs


Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach


Rethinking Value Function Learning for Generalization in Reinforcement Learning


Rethinking Variational Inference for Probabilistic Programs with Stochastic Support


Rethinking Verification for LLM Code Generation: From Generation to Testing


Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model


Rethinking Video Tokenization: A Conditioned Diffusion-based Approach


Rethinking Visual Content Refinement in Low-Shot CLIP Adaptation


Rethinking Visual Geo-localization for Large-Scale Applications


Rethinking Voxelization and Classification for 3D Object Detection


Rethinking Weight Decay For Efficient Neural Network Pruning


Rethinking Why Intermediate-Task Fine-Tuning Works


Rethinking Word-Level Auto-Completion in Computer-Aided Translation


Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective


Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables


Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications


Rethinking and Defending Protective Perturbation in Personalized Diffusion Models


Rethinking and Improving Multi-task Learning for End-to-end Speech Translation


Rethinking and Improving the Robustness of Image Style Transfer


Rethinking and Refining the Distinct Metric


Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination


Rethinking and Simplifying Bootstrapped Graph Latents


Rethinking cluster-conditioned diffusion models for label-free image synthesis


Rethinking conditional GAN training: An approach using geometrically structured latent manifolds


Rethinking deep active learning: Using unlabeled data at model training


Rethinking floating point for deep learning


Rethinking materials simulations: Blending direct numerical simulations with neural operators


Rethinking model prototyping through the MedMNIST+ dataset collection


Rethinking of Encoder-based Warm-start Methods in Hyperparameter Optimization


Rethinking recidivism through a causal lens


Rethinking skip connection model as a learnable Markov chain


Rethinking temporal self-similarity for repetitive action counting


Rethinking the Architecture Design for Efficient Generic Event Boundary Detection


Rethinking the Atmospheric Scattering-driven Attention via Channel and Gamma Correction Priors for Low-Light Image Enhancement


Rethinking the Augmentation Module in Contrastive Learning: Learning Hierarchical Augmentation Invariance with Expanded Views


Rethinking the Authorship Verification Experimental Setups


Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective


Rethinking the CSC Model for Natural Images


Rethinking the Construction of Effective Metrics for Understanding the Mechanisms of Pretrained Language Models


Rethinking the Data Annotation Process for Multi-view 3D Pose Estimation with Active Learning and Self-Training


Rethinking the Defense Against Free-rider Attack From the Perspective of Model Weight Evolving Frequency


Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization


Rethinking the Domain Gap in Near-infrared Face Recognition


Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning


Rethinking the Effectiveness of Graph Classification Datasets in Benchmarks for Assessing GNNs


Rethinking the Elementary Function Fusion for Single-Image Dehazing


Rethinking the Evaluation Protocol of Domain Generalization


Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models


Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMs


Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox


Rethinking the Event Coding Pipeline with Prompt Entailment


Rethinking the Expressive Power of GNNs via Graph Biconnectivity


Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation


Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks


Rethinking the Misalignment Problem in Dense Object Detection


Rethinking the Nested U-Net Approach: Enhancing Biomarker Segmentation with Attention Mechanisms and Multiscale Feature Fusion


Rethinking the Objectives of Extractive Question Answering


Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes


Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective


Rethinking the Reasonability of the Test Set for Simultaneous Machine Translation


Rethinking the Reference-based Distinctive Image Captioning


Rethinking the Reverse-engineering of Trojan Triggers


Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?


Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability


Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory


Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale


Rethinking the Route Towards Weakly Supervised Object Localization


Rethinking the Setting of Semi-supervised Learning on Graphs


Rethinking the Spatial Inconsistency in Classifier-Free Diffusion Guidance


Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective


Rethinking the Threat and Accessibility of Adversarial Attacks against Face Recognition Systems


Rethinking the Truly Unsupervised Image-to-Image Translation


Rethinking the Two-Stage Framework for Grounded Situation Recognition


Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection


Rethinking the Value of Gazetteer in Chinese Named Entity Recognition


Rethinking the adaptive relationship between Encoder Layers and Decoder Layers


Rethinking the compositionality of point clouds through regularization in the hyperbolic space


Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation


Rethinking the ill-posedness of the spectral function reconstruction -- why is it fundamentally hard and how Artificial Neural Networks can help


Rethinking the positive role of cluster structure in complex networks for link prediction tasks


Rethinking the transfer learning for FCN based polyp segmentation in colonoscopy


Rethinking the visual cues in audio-visual speaker extraction


Rethinking travel behavior modeling representations through embeddings


Rethinking with Retrieval: Faithful Large Language Model Inference


RethinkingTMSC: An Empirical Study for Target-Oriented Multimodal Sentiment Classification


Rethnicity: Predicting Ethnicity from Names


Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model


RetiFluidNet: A Self-Adaptive and Multi-Attention Deep Convolutional Network for Retinal OCT Fluid Segmentation


RetinaNet Object Detector based on Analog-to-Spiking Neural Network Conversion


RetinaQA: A Robust Knowledge Base Question Answering Model for both Answerable and Unanswerable Questions


Retinal Image Restoration using Transformer and Cycle-Consistent Generative Adversarial Network


Retinal Structure Detection in OCTA Image via Voting-based Multi-task Learning


Retinal Vessel Segmentation with Pixel-wise Adaptive Filters


Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement


Retinex-guided Histogram Transformer for Mask-free Shadow Removal


Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement


Retinexmamba: Retinex-based Mamba for Low-light Image Enhancement


RetinotopicNet: An Iterative Attention Mechanism Using Local Descriptors with Global Context


Retiring $Δ$DP: New Distribution-Level Metrics for Demographic Parity


Retraining-Free Merging of Sparse MoE via Hierarchical Clustering


Retraining-free Model Quantization via One-Shot Weight-Coupling Learning


Retrieval & Interaction Machine for Tabular Data Prediction


Retrieval Augmentation for Commonsense Reasoning: A Unified Approach


Retrieval Augmentation for Deep Neural Networks


Retrieval Augmented Code Generation and Summarization


Retrieval Augmented Generation Systems: Automatic Dataset Creation, Evaluation and Boolean Agent Setup


Retrieval Augmented Generation and Representative Vector Summarization for large unstructured textual data in Medical Education


Retrieval Augmented Generation based Large Language Models for Causality Mining


Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generation


Retrieval Augmented Time Series Forecasting


Retrieval Augmented Zero-Shot Text Classification


Retrieval Backward Attention without Additional Training: Enhance Embeddings of Large Language Models via Repetition


Retrieval Guided Unsupervised Multi-domain Image-to-Image Translation


Retrieval Head Mechanistically Explains Long-Context Factuality


Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models


Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models


Retrieval augmentation of large language models for lay language generation


Retrieval augmented text-to-SQL generation for epidemiological question answering using electronic health records


Retrieval for Extremely Long Queries and Documents with RPRS: a Highly Efficient and Effective Transformer-based Re-Ranker


Retrieval of Case 2 Water Quality Parameters with Machine Learning


Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context


Retrieval or Global Context Understanding? On Many-Shot In-Context Learning for Long-Context Evaluation


Retrieval-Augmented Decision Transformer: External Memory for In-context RL


Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech Synthesis


Retrieval-Augmented Diffusion Models for Time Series Forecasting


Retrieval-Augmented Dynamic Prompt Tuning for Incomplete Multimodal Learning


Retrieval-Augmented Generation for Code Summarization via Hybrid GNN


Retrieval-Augmented Generation with Hierarchical Knowledge


Retrieval-Augmented Generation-based Relation Extraction


Retrieval-Augmented Language Model for Extreme Multi-Label Knowledge Graph Link Prediction


Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation


Retrieval-Augmented Machine Translation with Unstructured Knowledge


Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training


Retrieval-Augmented Neural Field for HRTF Upsampling and Personalization


Retrieval-Augmented Open-Vocabulary Object Detection


Retrieval-Augmented Perception: High-Resolution Image Perception Meets Visual RAG


Retrieval-Augmented Score Distillation for Text-to-3D Generation


Retrieval-Based Transformer for Table Augmentation


Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language Model


Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System


Retrieval-Oriented Knowledge for Click-Through Rate Prediction


Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge


Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference


Retrieval-based Controllable Molecule Generation


Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments


Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis


Retrieval-style In-Context Learning for Few-shot Hierarchical Text Classification


RetrievalFuse: Neural 3D Scene Reconstruction with a Database


Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval


Retrieve and Refine: Exemplar-based Neural Comment Generation


Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval


Retrieve to Explain: Evidence-driven Predictions with Language Models


Retrieve, Generate, Evaluate: A Case Study for Medical Paraphrases Generation with Small Language Models


Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning


Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension


Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation


Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering


Retrieved Sequence Augmentation for Protein Representation Learning


Retriever-and-Memory: Towards Adaptive Note-Enhanced Retrieval-Augmented Generation


Retrieving Black-box Optimal Images from External Databases


Retrieving Complex Tables with Multi-Granular Graph Representation Learning


Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges


Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation


Retrieving Top Weighted Triangles in Graphs


Retrieving Users' Opinions on Social Media with Multimodal Aspect-Based Sentiment Analysis


Retrieving genuine nonlinear Raman responses in ultrafast spectroscopy via deep learning


Retrieving past quantum features with deep hybrid classical-quantum reservoir computing


Retrieving space-dependent polarization transformations via near-optimal quantum process tomography


Retrieving the Aerosol Complex Refractive Index using PyMieScatt: A Mie Computational Package with Visualization Capabilities


Retro-BLEU: Quantifying Chemical Plausibility of Retrosynthesis Routes through Reaction Template Sequence Analysis


Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentation


Retro-fallback: retrosynthetic planning in an uncertain world


Retro-li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization


RetroBridge: Modeling Retrosynthesis with Markov Bridges


RetroComposer: Composing Templates for Template-Based Retrosynthesis Prediction


RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations


RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets


RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation


RetroXpert: Decompose Retrosynthesis Prediction like a Chemist


Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations


Retrofitting Temporal Graph Neural Networks with Transformer


Retroformer: Pushing the Limits of Interpretable End-to-end Retrosynthesis Transformer


Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization


Retrograde-rotating exoplanets experience obliquity excitations in an eccentricity-enabled resonance


Retromorphic Testing: A New Approach to the Test Oracle Problem


Retrospective Analysis of Controversial Subtopics on COVID-19 in Japan


Retrospective Comparative Analysis of Prostate Cancer In-Basket Messages: Responses from Closed-Domain LLM vs. Clinical Teams


Retrospective Higher-Order Markov Processes for User Trails


Retrospective Uncertainties for Deep Models using Vine Copulas


Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation


Retrospex: Language Agent Meets Offline Reinforcement Learning Critic


Retrosynthesis Prediction with Conditional Graph Logic Network


Retrosynthetic Planning with Dual Value Networks


Retrosynthetic Planning with Experience-Guided Monte Carlo Tree Search


Return of EM: Entity-driven Answer Set Expansion for QA Evaluation


Return of Unconditional Generation: A Self-supervised Representation Generation Method


Return of the Encoder: Maximizing Parameter Efficiency for SLMs


Return to Lacan: an approach to digital twin mind with free energy principle


Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge


Returning to the Start: Generating Narratives with Related Endpoints


Retuve: Automated Multi-Modality Analysis of Hip Dysplasia with Open Source AI


Retweet-BERT: Political Leaning Detection Using Language Features and Information Diffusion on Social Networks


Reusability Report: Comparing gradient descent and monte carlo tree search optimization of quantum annealing schedules


Reusable Options through Gradient-based Meta Learning


Reusable specimen-level inference in computational pathology


Reuse-Aware Compilation for Zoned Quantum Architectures Based on Neutral Atoms


ReuseKNN: Neighborhood Reuse for Differentially-Private KNN-Based Recommendations


Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes


Reusing Convolutional Activations from Frame to Frame to Speed up Training and Inference


Reusing Convolutional Neural Network Models through Modularization and Composition


Reusing Deep Neural Network Models through Model Re-engineering


Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation


Reusing Softmax Hardware Unit for GELU Computation in Transformers


Reusing Weights in Subword-aware Neural Language Models


Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMT


Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation


RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network


RevCore: Review-augmented Conversational Recommendation


RevDet: Robust and Memory Efficient Event Detection and Tracking in Large News Feeds


RevMUX: Data Multiplexing with Reversible Adapters for Efficient LLM Batch Inference


RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuning


RevUp: Revise and Update Information Bottleneck for Event Representation


Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning


Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking


Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models


Revealing Disocclusions in Temporal View Synthesis through Infilling Vector Prediction


Revealing Fine-Grained Values and Opinions in Large Language Models


Revealing Floating-Point Accumulation Orders in Software/Hardware Implementations


Revealing Hidden Mechanisms of Cross-Country Content Moderation with Natural Language Processing


Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method


Revealing Networks: Understanding Effective Teacher Practices in AI-Supported Classrooms using Transmodal Ordered Network Analysis


Revealing Persona Biases in Dialogue Systems


Revealing Personality Traits: A New Benchmark Dataset for Explainable Personality Recognition on Dialogues


Revealing Preference in Popular Music Through Familiarity and Brain Response


Revealing Secrets in SPARQL Session Level


Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations


Revealing Vision-Language Integration in the Brain with Multimodal Networks


Revealing Vulnerabilities in Stable Diffusion via Targeted Attacks


Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks


Revealing and Mitigating Over-Attention in Knowledge Editing


Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing


Revealing and Mitigating the Local Pattern Shortcuts of Mamba


Revealing and Protecting Labels in Distributed Training


Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs)


Revealing asymmetry on midplane of proto-planetary disc through modelling of axisymmetric emission: methodology


Revealing hidden defects through stored energy measurements of radiation damage


Revealing hidden physical nonclassicality with nonnegative polynomials


Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data


Revealing intrinsic vortex-core states in Fe-based superconductors through machine-learning-driven discovery


Revealing microcanonical phases and phase transitions of strongly correlated electrons via time-averaged classical shadows


Revealing patterns in HIV viral load data and classifying patients via a novel machine learning cluster summarization method


Revealing quasi-excitations in the low-density homogeneous electron gas with model exchange-correlation kernels


Revealing the Barriers of Language Agents in Planning


Revealing the Chemical Structure of the Magellanic Clouds with APOGEE. I. Calculating Individual Stellar Ages of RGB Stars in the Large Magellanic Cloud


Revealing the Dark Matter Halo with Axion Direct Detection


Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness


Revealing the Dark Secrets of Masked Image Modeling


Revealing the Deceptiveness of Knowledge Editing: A Mechanistic Analysis of Superficial Editing


Revealing the Distributional Vulnerability of Discriminators by Implicit Generators


Revealing the Milky Way's Hidden Circumgalactic Medium with the COS Quasar Database for Galactic Absorption Lines


Revealing the Myth of Higher-Order Inference in Coreference Resolution


Revealing the Parallel Multilingual Learning within Large Language Models


Revealing the Parametric Knowledge of Language Models: A Unified Framework for Attribution Methods


Revealing the Power of Masked Autoencoders in Traffic Forecasting


Revealing the Shape of Genome Space via K-mer Topology


Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective


Revealing the Warm and Hot Halo Baryons via Thomson Scattering of Quasar Light


Revealing the canalizing structure of Boolean functions: Algorithms and applications


Revealing the determinants of gender inequality in urban cycling with large-scale data


Revealing the research landscape of Master's degrees via bibliometric analyses


Revealing the structure of language model capabilities


Revealing trends and persistent cycles of non-autonomous systems with operator-theoretic techniques: Applications to past and present climate dynamics


Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds


Revec: Program Rejuvenation through Revectorization


Revelations: A Decidable Class of POMDPs with Omega-Regular Objectives


Revenge of the Fallen? Recurrent Models Match Transformers at Predicting Human Language Comprehension Metrics


Revenue Maximization Under Sequential Price Competition Via The Estimation Of s-Concave Demand Functions


Revenue vs. Welfare: A Comprehensive Analysis of Strategic Trade-offs in Online Food Delivery Systems


Reverb: A Framework For Experience Replay


Reverberation Mapping of Two Luminous Quasars: the Broad-line Region Structure and Black Hole Mass


Reverberation-based Features for Sound Event Localization and Detection with Distance Estimation


Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images


Reverse Engineering Human Mobility in Large-scale Natural Disasters


Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images


Reverse Engineering of Imperceptible Adversarial Image Perturbations


Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning


Reverse Image Retrieval Cues Parametric Memory in Multimodal LLMs


Reverse Influential Community Search Over Social Networks (Technical Report)


Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness


Reverse Knowledge Distillation: Training a Large Model using a Small One for Retinal Image Matching on Limited Data


Reverse Map Projections as Equivariant Quantum Embeddings


Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item?


Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought


Reverse Operation based Data Augmentation for Solving Math Word Problems


Reverse Quantile-RK and its Application to Quantile-RK


Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?


Reverse Region-to-Entity Annotation for Pixel-Level Visual Entity Linking


Reverse engineering of CAD models via clustering and approximate implicitization


Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems


Reverse image filtering using total derivative approximation and accelerated gradient descent


Reverse-Engineering Information Presentations: Recovering Hierarchical Grouping from Layouts of Visual Elements


Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances"


Reverse-Engineering the Retrieval Process in GenIR Models


Reverse-engineering Bar Charts Using Neural Networks


Reversed Attention: On The Gradient Descent Of Attention Layers In GPT


Reversed in Time: A Novel Temporal-Emphasized Benchmark for Cross-Modal Video-Text Retrieval


Reversibility and Composition of Rewriting in Hierarchies


Reversible Colour Density Compression of Images using cGANs


Reversible Decoupling Network for Single Image Reflection Removal


Reversible Electrochemical Phase Change in Monolayer to Bulk MoTe2 by Ionic Liquid Gating


Reversible GANs for Memory-efficient Image-to-Image Translation


Reversible Graph Neural Network-based Reaction Distribution Learning for Multiple Appropriate Facial Reactions Generation


Reversible Jump Attack to Textual Classifiers with Modification Reduction


Reversible Jump PDMP Samplers for Variable Selection


Reversible and irreversible bracket-based dynamics for deep graph neural networks


Reversible molecular simulation for training classical and machine learning force fields


Reversible random number generation for adjoint Monte Carlo simulation of the heat equation


Reversible signal transmission in an active mechanical metamaterial


Reversing Unknown Quantum Transformations: Universal Quantum Circuit for Inverting General Unitary Operations


Reversing Unknown Qubit-Unitary Operation, Deterministically and Exactly


Reversing the Damage: A QP-Aware Transformer-Diffusion Approach for 8K Video Restoration under Codec Compression


Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation


Review Conversational Reading Comprehension


Review and Demonstration of a Mixture Representation for Simulation from Densities Involving Sums of Powers


Review and Perspective for Distance Based Trajectory Clustering


Review for Dynamic Prediction in Clinical Survival Analysis


Review of Hubble tension solutions with new SH0ES and SPT-3G data


Review of Learning-Assisted Power System Optimization


Review of Newman's Analytical Series on Disk Electrodes


Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision


Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal


Review of deep learning models for crypto price prediction: implementation and evaluation


Review of performance metrics of spin qubits in gated semiconducting nanostructures


Review of the ${\mathbf \Lambda}$(1405): A curious case of a strange-ness resonance


Review-Based Hyperbolic Cross-Domain Recommendation


Review-Driven Answer Generation for Product-Related Questions in E-Commerce


Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations


Review-Instruct: A Review-Driven Multi-Turn Conversations Generation Method for Large Language Models


Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation


Review-guided Helpful Answer Identification in E-commerce


ReviewRanker: A Semi-Supervised Learning Based Approach for Code Review Quality Estimation


ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis


ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile Applications


Reviewing BPMN as a Modeling Notation for CACAO Security Playbooks


Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review


Revise, Reason, and Recognize: LLM-Based Emotion Recognition via Emotion-Specific Prompts and ASR Error Correction


Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors


Revised Estimates of Ocean Surface Drag in Strong Winds


Revised Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks


Revised SCLP-simplex Algorithm with Application to Large-Scale Fluid Processing Networks


Revising Apetrei's bounding volume hierarchy construction algorithm to allow stackless traversal


Revising Properties of Planet-host Binary Systems I.: Methods and Pilot Study


Revising Properties of Planet-host Binary Systems II: Apparent Near-Earth Analog Planets in Binaries Are Often Sub-Neptunes


Revising deep learning methods in parking lot occupancy detection


Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing


Revision Transformers: Instructing Language Models to Change their Values


Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning


Revisit 1D Total Variation restoration problem with new real-time algorithms for signal and hyper-parameter estimations


Revisit Anything: Visual Place Recognition via Image Segment Retrieval


Revisit CP Tensor Decomposition: Statistical Optimality and Fast Convergence


Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training


Revisit Input Perturbation Problems for LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling Task


Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning


Revisit Time Series Classification Benchmark: The Impact of Temporal Information for Classification


Revisit What You See: Disclose Language Prior in Vision Tokens for Efficient Guided Decoding of LVLMs


Revisiting $L_q(0\leq q<1)$ Norm Regularized Optimization


Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited Learning


Revisiting 2-3 Red-Black Trees with a Pedagogically Sound yet Efficient Deletion Algorithm: The Parity-Seeking Delete Algorithm


Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices


Revisiting 3D LLM Benchmarks: Are We Really Testing 3D Capabilities?


Revisiting AGN Placement on the BPT Diagram: A Spectral Decomposition Approach


Revisiting Active Learning in the Era of Vision Foundation Models


Revisiting Active Sets for Gaussian Process Decoders


Revisiting Adaptive Cellular Recognition Under Domain Shifts: A Contextual Correspondence View


Revisiting Adversarial Perception Attacks and Defense Methods on Autonomous Driving Systems


Revisiting Adversarial Training at Scale


Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models


Revisiting Adversarial Training under Long-Tailed Distributions


Revisiting Adversarially Learned Injection Attacks Against Recommender Systems


Revisiting Anchor Mechanisms for Temporal Action Localization


Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data


Revisiting Attention for Multivariate Time Series Forecasting


Revisiting Automated Prompting: Are We Actually Doing Better?


Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch


Revisiting Bayesian Autoencoders with MCMC


Revisiting Bayesian Optimization in the light of the COCO benchmark


Revisiting Bellman Errors for Offline Model Selection


Revisiting Binary Local Image Description for Resource Limited Devices


Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?


Revisiting Bounded-Suboptimal Safe Interval Path Planning


Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem


Revisiting CLIP: Efficient Alignment of 3D MRI and Tabular Data using Domain-Specific Foundation Models


Revisiting CNNs for Trajectory Similarity Learning


Revisiting Catastrophic Forgetting in Large Language Model Tuning


Revisiting Cellular Throughput Prediction over the Edge: Collaborative Multi-device, Multi-network in-situ Learning


Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head


Revisiting Challenges in Data-to-Text Generation with Fact Grounding


Revisiting Character-level Adversarial Attacks for Language Models


Revisiting Code Search in a Two-Stage Paradigm


Revisiting Compactness for District Plans


Revisiting Computer-Aided Tuberculosis Diagnosis


Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images


Revisiting Context Aggregation for Image Matting


Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations


Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics


Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings


Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck


Revisiting CroPA: A Reproducibility Study and Enhancements for Cross-Prompt Adversarial Transferability in Vision-Language Models


Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation


Revisiting Cross-Modal Knowledge Distillation: A Disentanglement Approach for RGBD Semantic Segmentation


Revisiting CycleGAN for semi-supervised segmentation


Revisiting Data Augmentation for Ultrasound Images


Revisiting Data Augmentation in Deep Reinforcement Learning


Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect


Revisiting Data-Free Knowledge Distillation with Poisoned Teachers


Revisiting Day-ahead Electricity Price: Simple Model Save Millions


Revisiting Decomposable Submodular Function Minimization with Incidence Relations


Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation


Revisiting Deep Ensemble Uncertainty for Enhanced Medical Anomaly Detection


Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective


Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection


Revisiting Deep Generalized Canonical Correlation Analysis


Revisiting Deep Learning for Variable Type Recovery


Revisiting Deep Neural Network Test Coverage from the Test Effectiveness Perspective


Revisiting Demonstration Selection Strategies in In-Context Learning


Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization


Revisiting Design Choices in Proximal Policy Optimization


Revisiting Discriminative vs. Generative Classifiers: Theory and Implications


Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme


Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery


Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction


Revisiting Document Representations for Large-Scale Zero-Shot Learning


Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective


Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling


Revisiting Dynamic Convolution via Matrix Decomposition


Revisiting Early Detection of Sexual Predators via Turn-level Optimization


Revisiting End-to-End Learning with Slide-level Supervision in Computational Pathology


Revisiting Energy-Based Model for Out-of-Distribution Detection


Revisiting Ensembling in One-Shot Federated Learning


Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?


Revisiting Essential and Nonessential Settings of Evidential Deep Learning


Revisiting Event Argument Extraction: Can EAE Models Learn Better When Being Aware of Event Co-occurrences?


Revisiting Event Study Designs: Robust and Efficient Estimation


Revisiting Fake News Detection: Towards Temporality-aware Evaluation by Leveraging Engagement Earliness


Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction


Revisiting Few-Shot Learning from a Causal Perspective


Revisiting Few-Shot Object Detection with Vision-Language Models


Revisiting File Context for Source Code Summarization


Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach


Revisiting Fully Convolutional Geometric Features for Object 6D Pose Estimation


Revisiting FunnyBirds evaluation framework for prototypical parts networks


Revisiting Gaussian Neurons for Online Clustering with Unknown Number of Clusters


Revisiting Generative Adversarial Networks for Binary Semantic Segmentation on Imbalanced Datasets


Revisiting Generative Commonsense Reasoning: A Pre-Ordering Approach


Revisiting Generative Policies: A Simpler Reinforcement Learning Algorithmic Perspective


Revisiting Gradient Descent: A Dual-Weight Method for Improved Learning


Revisiting Grammatical Error Correction Evaluation and Beyond


Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum


Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum


Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment


Revisiting Heterophily For Graph Neural Networks


Revisiting Hidden Representations in Transfer Learning for Medical Imaging


Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction


Revisiting Hierarchical Text Classification: Inference and Metrics


Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness


Revisiting Image Captioning Training Paradigm via Direct CLIP-based Optimization


Revisiting Image Deblurring with an Efficient ConvNet


Revisiting Implicit Neural Representations in Low-Level Vision


Revisiting In-context Learning Inference Circuit in Large Language Models


Revisiting Inferential Benchmarks for Knowledge Graph Completion


Revisiting Instruction Fine-tuned Model Evaluation to Guide Industrial Applications


Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective


Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning


Revisiting Knowledge Distillation for Autoregressive Language Models


Revisiting Knowledge Distillation under Distribution Shift


Revisiting Knowledge Distillation via Label Smoothing Regularization


Revisiting Knowledge Distillation: An Inheritance and Exploration Framework


Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?


Revisiting Language Encoding in Learning Multilingual Representations


Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network


Revisiting Lightweight Compiler Provenance Recovery on ARM Binaries


Revisiting Local Descriptor for Improved Few-Shot Classification


Revisiting Locality in Binary-Integer Representations


Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance


Revisiting Locally Supervised Learning: an Alternative to End-to-end Training


Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping


Revisiting Loss Modelling for Unstructured Pruning


Revisiting Lossless Convexification: Theoretical Guarantees for Discrete-time Optimal Control Problems


Revisiting MAB based approaches to recursive delegation


Revisiting Machine Learning based Test Case Prioritization for Continuous Integration


Revisiting Main Memory-Based Covert and Side Channel Attacks in the Context of Processing-in-Memory


Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms


Revisiting Memory Efficient Kernel Approximation: An Indefinite Learning Perspective


Revisiting Meta-evaluation for Grammatical Error Correction


Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation


Revisiting Model's Uncertainty and Confidences for Adversarial Example Detection


Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective


Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations


Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective


Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens


Revisiting Negation in Neural Machine Translation


Revisiting Network Perturbation for Semi-Supervised Semantic Segmentation


Revisiting Neuron Coverage Metrics and Quality of Deep Neural Networks


Revisiting Non-Acyclic GFlowNets in Discrete Environments


Revisiting Non-Autoregressive Transformers for Efficient Image Synthesis


Revisiting Non-Autoregressive Translation at Scale


Revisiting Non-Specific Syndromic Surveillance


Revisiting Non-separable Binary Classification and its Applications in Anomaly Detection


Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models


Revisiting Optimism and Model Complexity in the Wake of Overparameterized Machine Learning


Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection


Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature


Revisiting PSF models: unifying framework and high-performance implementation


Revisiting Parameter-Efficient Tuning: Are We Really There Yet?


Revisiting Parametricity: Inductives and Uniformity of Propositions


Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages


Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data


Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition


Revisiting Pre-training in Audio-Visual Learning


Revisiting Pretraining Objectives for Tabular Deep Learning


Revisiting Projection-based Data Transfer for Cross-Lingual Named Entity Recognition in Low-Resource Languages


Revisiting RGBT Tracking Benchmarks from the Perspective of Modality Validity: A New Benchmark, Problem, and Method


Revisiting Random Walks for Learning on Graphs


Revisiting Random Weight Perturbation for Efficiently Improving Generalization


Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering


Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training


Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method


Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models


Revisiting ResNets: Improved Training and Scaling Strategies


Revisiting Restarts of CDCL: Should the Search Information be Preserved?


Revisiting Robust Model Fitting Using Truncated Loss


Revisiting Rotation Averaging: Uncertainties and Robust Losses


Revisiting Sample Size Determination in Natural Language Understanding


Revisiting Scene Text Recognition: A Data Perspective


Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective


Revisiting Self-Supervised Monocular Depth Estimation


Revisiting Self-Training for Neural Sequence Generation


Revisiting Semantic Representation and Tree Search for Similar Question Retrieval


Revisiting Sentence Union Generation as a Testbed for Text Consolidation


Revisiting Sentiment Analysis for Software Engineering in the Era of Large Language Models


Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory


Revisiting Simple Neural Networks for Learning Representations of Knowledge Graphs


Revisiting Simple Neural Probabilistic Language Models


Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook


Revisiting Single Image Reflection Removal In the Wild


Revisiting Skin Tone Fairness in Dermatological Lesion Classification


Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution


Revisiting Sparse Convolutional Model for Visual Recognition


Revisiting Sparse Matrix Coloring and Bicoloring


Revisiting Sparse Retrieval for Few-shot Entity Linking


Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays


Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers


Revisiting Stereo Triangulation in UAV Distance Estimation


Revisiting Supervision for Continual Representation Learning


Revisiting Surgical Instrument Segmentation Without Human Intervention: A Graph Partitioning View


Revisiting Synthetic Human Trajectories: Imitative Generation and Benchmarks Beyond Datasaurus


Revisiting Tampered Scene Text Detection in the Era of Generative AI


Revisiting Temporal Alignment for Video Restoration


Revisiting Temporal Modeling for Video Super-resolution


Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings


Revisiting The Classics: A Study on Identifying and Rectifying Gender Stereotypes in Rhymes and Poems


Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis


Revisiting The Spectral and Timing Properties of NGC 4151


Revisiting Token Dropping Strategy in Efficient BERT Pretraining


Revisiting Token Pruning for Object Detection and Instance Segmentation


Revisiting Training-Inference Trigger Intensity in Backdoor Attacks


Revisiting Training-free NAS Metrics: An Efficient Training-based Method


Revisiting Transactional Statistics of High-scalability Blockchain


Revisiting Transformer-based Models for Long Document Classification


Revisiting Tri-training of Dependency Parsers


Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers


Revisiting Unsupervised Learning for Defect Prediction


Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks


Revisiting Unsupervised Relation Extraction


Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective


Revisiting Video Quality Assessment from the Perspective of Generalization


Revisiting Video Saliency: A Large-scale Benchmark and a New Model


Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation


Revisiting Weakly Supervised Pre-Training of Visual Perception Models


Revisiting Weight Averaging for Model Merging


Revisiting Weighted Aggregation in Federated Learning with Neural Networks


Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective


Revisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias


Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark


Revisiting adversarial training for the worst-performing class


Revisiting and Benchmarking Graph Autoencoders: A Contrastive Learning Perspective


Revisiting and Improving Retrieval-Augmented Deep Assertion Generation


Revisiting and Improving Scoring Fusion for Spoofing-aware Speaker Verification Using Compositional Data Analysis


Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation


Revisiting and modeling power-law distributions in empirical outage data of power systems


Revisiting boundary layer flows of viscoelastic fluids


Revisiting consistency for semi-supervised semantic segmentation


Revisiting convolutive blind source separation for identifying spiking motor neuron activity: From theory to practice


Revisiting gender bias research in bibliometrics: Standardizing methodological variability using Scholarly Data Analysis (SoDA) Cards


Revisiting graph neural networks and distance encoding from a practical view


Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories


Revisiting inverse Hessian vector products for calculating influence functions


Revisiting joint decoding based multi-talker speech recognition with DNN acoustic model


Revisiting k-NN for Fine-tuning Pre-trained Language Models


Revisiting local branching with a machine learning lens


Revisiting lp-constrained Softmax Loss: A Comprehensive Study


Revisiting minimum description length complexity in overparameterized models


Revisiting non-English Text Simplification: A Unified Multilingual Benchmark


Revisiting non-linearity in binary black hole mergers


Revisiting pseudo-Dirac neutrino scenario after recent solar neutrino data


Revisiting semi-supervised learning in the era of foundation models


Revisiting spatio-temporal layouts for compositional action recognition


Revisiting ssFix for Better Program Repair


Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective


Revisiting the Approximate Carathéodory Problem via the Frank-Wolfe Algorithm


Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond


Revisiting the Auxiliary Data in Backdoor Purification


Revisiting the Calibration of Modern Neural Networks


Revisiting the Complexity of and Algorithms for the Graph Traversal Edit Distance and Its Variants


Revisiting the Critical Factors of Augmentation-Invariant Representation Learning


Revisiting the Design of In-Memory Dynamic Graph Storage


Revisiting the Effects of Leakage on Dependency Parsing


Revisiting the Emission Line Source Detection Problem in Integral Field Spectroscopic Data


Revisiting the Encoding of Satellite Image Time Series


Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off


Revisiting the Folklore Algorithm for Random Access to Grammar-Compressed Strings


Revisiting the Fragility of Influence Functions


Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation


Revisiting the Green-Kubo relation for friction in nanofluidics


Revisiting the Impact of Pursuing Modularity for Code Generation


Revisiting the Integration of Convolution and Attention for Vision Backbone


Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors


Revisiting the Loss Weight Adjustment in Object Detection


Revisiting the Message Passing in Heterophilous Graph Neural Networks


Revisiting the Minimalist Approach to Offline Reinforcement Learning


Revisiting the Negative Data of Distantly Supervised Relation Extraction


Revisiting the Onsets and Frames Model with Additive Attention


Revisiting the Optimality of Word Lengths


Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets


Revisiting the Reliability of Psychological Scales on Large Language Models


Revisiting the Robustness of Watermarking to Paraphrasing Attacks


Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study


Revisiting the Role of Language Priors in Vision-Language Models


Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes


Revisiting the Schedule Graph Generation for the Exact and Sustainable Analysis of Non-preemptive Scheduling


Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification


Revisiting the Solution of Meta KDD Cup 2024: CRAG


Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?


Revisiting the Thickness of the Air-Water Interface from Two Extremes of Interface Hydrogen Bond Dynamics


Revisiting the Threat Space for Vision-based Keystroke Inference Attacks


Revisiting the Trade-off between Accuracy and Robustness via Weight Distribution of Filters


Revisiting the Vector Space Model: Sparse Weighted Nearest-Neighbor Method for Extreme Multi-Label Classification


Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation


Revisiting the attacker's knowledge in inference attacks against Searchable Symmetric Encryption


Revisiting the details when evaluating a visual tracker


Revisiting the hydrodynamic modulation of short surface waves by longer waves


Revisiting the relevance of traditional genres: a network analysis of fiction readers' preferences


Revisiting the role of friction coefficients in granular collapses: confrontation of 3-D non-smooth simulations with experiments


Revisiting the thorny issue of missing values in single-cell proteomics


Revisiting, Benchmarking and Exploring API Recommendation: How Far Are We?


Revitalising the Single Batch Environment: A 'Quest' to Achieve Fairness and Efficiency


Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling


Reviving Undersampling for Long-Tailed Learning


Reviving and Improving Recurrent Back-Propagation


Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs


Reviving the Lieb-Schultz-Mattis Theorem in Open Quantum Systems


Reviving the Vortex Particle Method: A Stable Formulation for Meshless Large Eddy Simulation


Revizor: A Data-Driven Approach to Automate Frequent Code Changes Based on Graph Matching


Revizor: Testing Black-box CPUs against Speculation Contracts


Revolutionizing API Documentation through Summarization


Revolutionizing Database Q&A with Large Language Models: Comprehensive Benchmark and Evaluation


Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model


Reward Certification for Policy Smoothed Reinforcement Learning


Reward Collapse in Aligning Large Language Models


Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization


Reward Delay Attacks on Deep Reinforcement Learning


Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care


Reward Design for Justifiable Sequential Decision-Making


Reward Dropout Improves Control: Bi-objective Perspective on Reinforced LM


Reward Engineering for Generating Semi-structured Explanation


Reward Estimation for Variance Reduction in Deep Reinforcement Learning


Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation


Reward Learning from Multiple Feedback Types


Reward Learning with Intractable Normalizing Functions


Reward Machines for Deep RL in Noisy and Uncertain Environments


Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning


Reward Model Ensembles Help Mitigate Overoptimization


Reward Modeling with Weak Supervision for Language Models


Reward Optimization for Neural Machine Translation with Learned Metrics


Reward Shaping for Human Learning via Inverse Reinforcement Learning


Reward Shaping to Mitigate Reward Hacking in RLHF


Reward Systems for Trustworthy Medical Federated Learning


Reward-Augmented Data Enhances Direct Preference Alignment of LLMs


Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty Environments


Reward-Free Curricula for Training Robust World Models


Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design


Reward-Machine-Guided, Self-Paced Reinforcement Learning


Reward-Reinforced Reinforcement Learning for Multi-agent Systems


Reward-SQL: Boosting Text-to-SQL via Stepwise Reasoning and Process-Supervised Rewards


Reward-Weighted Regression Converges to a Global Optimum


Reward-based Input Construction for Cross-document Relation Extraction


Reward-free World Models for Online Imitation Learning


RewardAnything: Generalizable Principle-Following Reward Models


RewardSDS: Aligning Score Distillation via Reward-Weighted Sampling


Rewarded Region Replay (R3) for Policy Learning with Discrete Action Space


Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards


Rewarding Coreference Resolvers for Being Consistent with World Knowledge


Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment


Reweighted Infrared Patch-Tensor Model With Both Non-Local and Local Priors for Single-Frame Small Target Detection


Reweighting Monte Carlo Predictions and Automated Fragmentation Variations in Pythia 8


Reweighting Strategy based on Synthetic Data Identification for Sentence Similarity


Reweighting of molecular simulations with explicit-solvent SAXS restraints elucidates ion-dependent RNA ensembles


Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions


Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models


Rewiring What-to-Watch-Next Recommendations to Reduce Radicalization Pathways


Rewrite to Jailbreak: Discover Learnable and Transferable Implicit Harmfulness Instruction


Rewriting Pre-Training Data Boosts LLM Performance in Math and Code


Rewriting Theory for the Life Sciences: A Unifying Theory of CTMC Semantics (Long version)


Rewriting the Budget: A General Framework for Black-Box Attacks Under Cost Asymmetry


Rewriting the Code: A Simple Method for Large Language Model Augmented Code Search


ReynoldsFlow: Exquisite Flow Estimation via Reynolds Transport Theorem


RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction


Rgtsvm: Support Vector Machines on a GPU in R


Rhapsody: A Dataset for Highlight Detection in Podcasts


Rheology of three-phase suspensions determined via dam-break experiments


Rhombic Grids Reduce the Number of Voxels in Fast Pulse-Echo Ultrasound Imaging


Rhythm Dungeon: A Blockchain-based Music Roguelike Game


Rhythm-Flexible Voice Conversion without Parallel Data Using Cycle-GAN over Phoneme Posteriorgram Sequences


RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention


RhythmMamba: Fast Remote Physiological Measurement with Arbitrary Length Videos


Rhythmic sharing: A bio-inspired paradigm for zero-shot adaptive learning in neural networks


Rhythms of the collective brain: Metastable synchronization and cross-scale interactions in connected multitudes


RiDDLE: Reversible and Diversified De-identification with Latent Encryptor


RiLACS: Risk-Limiting Audits via Confidence Sequences


RiM: Record, Improve and Maintain Physical Well-being using Federated Learning


RiNALMo: General-Purpose RNA Language Models Can Generalize Well on Structure Prediction Tasks


RiSAWOZ: A Large-Scale Multi-Domain Wizard-of-Oz Dataset with Rich Semantic Annotations for Task-Oriented Dialogue Modeling


RiTTA: Modeling Event Relations in Text-to-Audio Generation


RiWalk: Fast Structural Node Embedding via Role Identification


RiboDiffusion: Tertiary Structure-based RNA Inverse Folding with Generative Diffusion Models


RicMonk: A Three-Link Brachiation Robot with Passive Grippers for Energy-Efficient Brachiation


Ricci-Notation Tensor Framework for Model-based Approaches to Imaging


Rich Action-semantic Consistent Knowledge for Early Action Prediction


Rich Event Modeling for Script Event Prediction


Rich Feature Construction for the Optimization-Generalization Dilemma


Rich Specifications for Ethereum Smart Contract Verification


Richardson-Lucy deconvolution with a spatially Variant point-spread function of Chandra: Supernova Remnant Cassiopeia A as an Example


Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy


Richer Countries and Richer Representations


Richer Output for Richer Countries: Uncovering Geographical Disparities in Generated Stories and Travel Recommendations


Richer priors for infinitely wide multi-layer perceptrons


Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis


Ridge Regression: Structure, Cross-Validation, and Sketching


RidgeBase: A Cross-Sensor Multi-Finger Contactless Fingerprint Dataset