Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Montreal, Canada
16-22 August 2025with satellite event in Guangzhou, China 29-31 August 2025
Edited by James Kwok
Sponsored by
International Joint Conferences on Artifical Intelligence (IJCAI)
Published by
International Joint Conferences on Artificial Intelligence
Copyright © 2025 International Joint Conferences on Artificial Intelligence
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.
IJCAI Secretary-Treasurer: Kristian Kersting, Computer Science Department, Technical University of Darmstadt, Hochschulstraße 10, D-64289 Darmstadt, Germany
IJCAI Executive Director - IJCAI Executive Secretary Ms. Vesna Sabljakovic-Fritz, Vienna University of Technology, Institute of Discrete Mathematics and Geometry, E104 Wiedner Hauptstr. 8-10, A-1040 Vienna, Austria
ISBN (Online): 978-1-956792-06-5
Content
Main Track
Agent-based and Multi-agent Systems
Coalition Obstruction Temporal Logic: A New Obstruction Logic to Reason About Demon Coalitions
Optimal Distributed Training With Co-Adaptive Data Parallelism in Heterogeneous Environments
Co-Learning of Strategy and Structure Achieves Full Cooperation in Complex Networks with Dynamical Linking
SocialMP: Learning Social Aware Motion Patterns via Additive Fusion for Pedestrian Trajectory Prediction
L2M2: A Hierarchical Framework Integrating Large Language Model and Multi-agent Reinforcement Learning
Resistance is Futile: Gradually Declining Immunity Retains the Exponential Duration of Immunity-Free Diffusion
MIRROR: Multi-agent Intra- and Inter-Reflection for Optimized Reasoning in Tool Learning
Strategies, Credences, and Shannon Entropy: Reasoning about Strategic Uncertainty in Stochastic Environments
Approximate Verification of Strategic Abilities under Imperfect Information Using Local Models
RoLocMe: A Robust Multi-agent Source Localization System with Learning-based Map Estimation
Combining Deep Reinforcement Learning and Search with Generative Models for Game-Theoretic Opponent Modeling
Deep Learning-Based Pedestrian Simulation with Limited Real-World Training Data: An Evaluation Framework
Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
Beyond Winning Strategies: Admissible and Admissible Winning Strategies for Quantitative Reachability Games
Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences
Simulating Misinformation Diffusion on Social Media Through CoNVaI: A Textual- and Agent-Based Diffusion Model
Synthesis of Communication Policies for Multi-Agent Systems Robust to Communication Restrictions
CoderAgent: Simulating Student Behavior for Personalized Programming Learning with Large Language Models
Formal Synthesis of Safe Kolmogorov-Arnold Network Controllers with Barrier Certificates
MSMAR-RL: Multi-Step Masked-Attention Recovery Reinforcement Learning for Safe Maneuver Decision in High-Speed Pursuit-Evasion Game
Evaluating and Mitigating Linguistic Discrimination in Large Language Models: Perspectives on Safety Equity and Knowledge Equity
Cyclic Vision-Language Manipulator: Towards Reliable and Fine-Grained Image Interpretation for Automated Report Generation
Efficient Counterexample-Guided Fairness Verification and Repair of Neural Networks Using Satisfiability Modulo Convex Programming
OMS: One More Step Noise Searching to Enhance Membership Inference Attacks for Diffusion Models
Priority Guided Explanation for Knowledge Tracing with Dual Ranking and Similarity Consistency
FADE: Towards Fairness-aware Data Generation for Domain Generalization via Classifier-Guided Score-based Diffusion Models
VeRecycle: Reclaiming Guarantees from Probabilistic Certificates for Stochastic Dynamical Systems after Change
Towards Safer Pretraining: Analyzing and Filtering Harmful Content in Webscale Datasets for Responsible LLMs
Feint and Attack: Jailbreaking and Protecting LLMs via Attention Distribution Modeling
SAP: Privacy-Preserving Fine-Tuning on Language Models with Split-and-Privatize Framework
ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers
MVP-CBM: Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification
Weakly-supervised Audio Temporal Forgery Localization via Progressive Audio-language Co-learning Network
Fine-grained Prompt Screening: Defending Against Backdoor Attack on Text-to-Image Diffusion Models
Rethinking Removal Attack and Fingerprinting Defense for Model Intellectual Property Protection: A Frequency Perspective
DFCA: Disentangled Feature Contrastive Learning and Augmentation for Fairer Dermatological Diagnostics
Why the Agent Made that Decision: Contrastive Explanation Learning for Reinforcement Learning
Top-I2P: Explore Open-Domain Image-to-Point Cloud Registration Using Topology Relationship
LensNet: An End-to-End Learning Framework for Empirical Point Spread Function Modeling and Lensless Imaging Reconstruction
Towards Region-Adaptive Feature Disentanglement and Enhancement for Small Object Detection
Towards VLM-based Hybrid Explainable Prompt Enhancement for Zero-Shot Industrial Anomaly Detection
IterMeme: Expert-Guided Multimodal LLM for Interactive Meme Creation with Layout-Aware Generation
A Medical Image Classification Network Based on Multi-View Consistent Momentum Contrastive Learning
The Devil is in Fine-tuning and Long-tailed Problems: A New Benchmark for Scene Text Detection
Instructing Text-to-Image Diffusion Models via Classifier-Guided Semantic Optimization
MonoMixer: Marrying Convolution and Vision Transformer for Efficient Self-Supervised Monocular Depth Estimation
Inter3D: A Benchmark and Strong Baseline for Human-Interactive 3D Object Reconstruction
Categorical Attention: Fine-grained Language-guided Noise Filtering Network for Occluded Person Re-Identification
HSRMamba: Contextual Spatial-Spectral State Space Model for Single Hyperspectral Image Super-Resolution
Enhancing Mixture of Experts with Independent and Collaborative Learning for Long-Tail Visual Recognition
MC3D-AD: A Unified Geometry-aware Reconstruction Model for Multi-category 3D Anomaly Detection
External Memory Matters: Generalizable Object-Action Memory for Retrieval-Augmented Long-Term Video Understanding
Diff-LMM: Diffusion Teacher-Guided Spatio-Temporal Perception for Video Large Multimodal Models
Richer Semantics, Better Alignment: Aligning Visual Features with Explicit and Enriched Semantics for Visible-Infrared Person Re-Identification
Mask Does Not Matter: A Unified Latent Diffusion-Enhanced Framework for Mask-Free Virtual Try-On
Unleashing the Semantic Adaptability of Controlled Diffusion Model for Image Colorization
MAGE: Multimodal Alignment and Generation Enhancement via Bridging Visual and Semantic Spaces
Mixture-of-Queries Transformer: Camouflaged Instance Segmentation via Queries Cooperation and Frequency Enhancement
DDPA-3DVG: Vision-Language Dual-Decoupling and Progressive Alignment for 3D Visual Grounding
GPI-Net: Gestalt-Guided Parallel Interaction Network via Orthogonal Geometric Consistency for Robust Point Cloud Registration
Shaping a Stabilized Video by Mitigating Unintended Changes for Concept-Augmented Video Editing
DcDsDiff: Dual-Conditional and Dual-Stream Diffusion Model for Generative Image Tampering Localization
Exploiting Position Information in Convolutional Kernels for Structural Re-parameterization
Beyond Feature Mapping GAP: Integrating Real HDRTV Priors for Superior SDRTV-to-HDRTV Conversion
Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
Boosting Visual Knowledge-Intensive Training for LVLMs Through Causality-Driven Visual Object Completion
Spotlighting Partially Visible Cinematic Language for Video-to-Audio Generation via Self-distillation
ADC-GS: Anchor-Driven Deformable and Compressed Gaussian Splatting for Dynamic Scene Reconstruction
Human Motion Capture from Loose and Sparse Inertial Sensors with Garment-aware Diffusion Models
Optical Flow Estimation for Tiny Objects: New Problem, Specialized Benchmark, and Bioinspired Scheme
SeqPose: An End-to-End Framework to Unify Single-frame and Video-based RGB Category-Level Pose Estimation
IE-PMMA:Point Cloud Completion Through Inverse Edge-aware Upsampling and Precise Multi-Modal Feature Alignment
Concentrate on Weakness: Mining Hard Prototypes for Few-Shot Medical Image Segmentation
Exploring the Frontiers of Animation Video Generation in the Sora Era: Method, Dataset and Benchmark
Object-Level Backdoor Attacks in RGB-T Semantic Segmentation with Cross-Modality Trigger Optimization
UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block
Projection, Interaction and Fusion: A Progressive Difference Fusion Network for Salient Object Detection
Data Poisoning Attack Defense and Evolutionary Domain Adaptation for Federated Medical Image Segmentation
Towards Regularized Mixture of Predictions for Class-Imbalanced Semi-Supervised Facial Expression Recognition
ESBN: Estimation Shift of Batch Normalization for Source-free Universal Domain Adaptation
Preventing Latent Diffusion Model-Based Image Mimicry via Angle Shifting and Ensemble Learning
Tackling Long-Tailed Data Challenges in Spiking Neural Networks via Heterogeneous Knowledge Distillation
Temporal Consistency Constrained Transferable Adversarial Attacks with Background Mixup for Action Recognition
Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking
GarmentDiffusion: 3D Garment Sewing Pattern Generation with Multimodal Diffusion Transformers
A Timestep-Adaptive Frequency-Enhancement Framework for Diffusion-based Image Super-Resolution
PatternCIR Benchmark and TisCIR: Advancing Zero-Shot Composed Image Retrieval in Remote Sensing
MGCA-Net: Multi-Graph Contextual Attention Network for Two-View Correspondence Learning
GLDiTalker: Speech-Driven 3D Facial Animation with Graph Latent Diffusion Transformer
Language-Guided Hybrid Representation Learning for Visual Grounding on Remote Sensing Images
SyncGaussian: Stable 3D Gaussian-Based Talking Head Generation with Enhanced Lip Sync via Discriminative Speech Features
Fusion of Granular-Ball Visual Spatial Representations for Enhanced Facial Expression Recognition
Squeezing Context into Patches: Towards Memory-Efficient Ultra-High Resolution Semantic Segmentation
SOTA: Spike-Navigated Optimal TrAnsport Saliency Region Detection in Composite-bias Videos
Template3D-AD: Point Cloud Template Matching Method Based on Center Points for 3D Anomaly Detection
From Sparse to Complete: Semantic Understanding Based on Stroke Evolution in On-the-fly Sketch-based Image Retrieval
OT-DETECTOR: Delving into Optimal Transport for Zero-shot Out-of-Distribution Detection
SyncAnimation: A Real-Time End-to-End Framework for Audio-Driven Human Pose and Talking Head Animation
CrossVTON: Mimicking the Logic Reasoning on Cross-Category Virtual Try-On Guided by Tri-Zone Priors
Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restoration
EfficientPIE: Real-Time Prediction on Pedestrian Crossing Intention with Sole Observation
Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance
ExpTalk: Diverse Emotional Expression via Adaptive Disentanglement and Refined Alignment for Speech-Driven 3D Facial Animation
BankTweak: Adversarial Attack Against Multi-Object Trackers by Manipulating Feature Banks
MS-DPPs: Multi-Source Determinantal Point Processes for Contextual Diversity Refinement of Composite Attributes in Text to Image Retrieval
CMFS: CLIP-Guided Modality Interaction for Mitigating Noise in Multi-Modal Image Fusion and Segmentation
Dual-Perspective United Transformer for Object Segmentation in Optical Remote Sensing Images
Wave-wise Discriminative Tracking by Phase-Amplitude Separation, Augmentation and Mixture
BRIGHT-VO: Brightness-Guided Hybrid Transformer for Visual Odometry with Multi-modality Refinement Module
METOR: A Unified Framework for Mutual Enhancement of Objects and Relationships in Open-vocabulary Video Visual Relationship Detection
Boosting Zero-shot Stereo Matching Using Large-Scale Mixed Images Sources in the Real World
Deep Opinion-Unaware Blind Image Quality Assessment by Learning and Adapting from Multiple Annotators
Few-Shot Incremental Multi-modal Learning via Touch Guidance and Imaginary Vision Synthesis
ElaD-Net: An Elastic Semantic Decoupling Network for Lesion Segmentation in Breast Ultrasound Images
Advancing Stain Transfer for Multi-Biomarkers: A Human Annotation-Free Method Based on Auxiliary Task Supervision
Pre-defined Keypoints Promote Category-level Articulation Pose Estimation via Multi-Modal Alignment
SCOUT: Semi-supervised Camouflaged Object Detection by Utilizing Text and Adaptive Data Selection
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot Learning
AttentionDrag: Exploiting Latent Correlation Knowledge in Pre-trained Diffusion Models for Image Editing
RAMer: Reconstruction-based Adversarial Model for Multi-party Multi-modal Multi-label Emotion Recognition
DPMamba: Distillation Prompt Mamba for Multimodal Remote Sensing Image Classification with Missing Modalities
Do You Steal My Model? Signature Diffusion Embedded Dual-Verification Watermarking for Protecting Intellectual Property of Hyperspectral Image Classification Models
BEVTrack: A Simple and Strong Baseline for 3D Single Object Tracking in Bird's-Eye View
DriftRemover: Hybrid Energy Optimizations for Anomaly Images Synthesis and Segmentation
Self-Classification Enhancement and Correction for Weakly Supervised Object Detection
SCVBench: A Benchmark with Multi-turn Dialogues for Story-Centric Video Understanding
G3PT: Unleash the Power of Autoregressive Modeling in 3D Generation via Cross-Scale Querying Transformer
Multimodal Prior Learning with Double Constraint Alignment for Snapshot Spectral Compressive Imaging
CSF-GAN: Cross-modal Semantic Fusion-based Generative Adversarial Network for Text-guided Image Inpainting
HyperTrans: Efficient Hypergraph-Driven Cross-Domain Pattern Transfer in Image Anomaly Detection
Towards Micro-Action Recognition with Limited Annotations: An Asynchronous Pseudo Labeling and Training Approach
Balancing Invariant and Specific Knowledge for Domain Generalization with Online Knowledge Distillation
Bi-DiffCD: Bidirectional Diffusion Guided Collaborative Change Detection for Arbitrary-Modal Remote Sensing Images
Enhancing Multimodal Model Robustness Under Missing Modalities via Memory-Driven Prompt Learning
RPMIL: Rethinking Uncertainty-Aware Probabilistic Multiple Instance Learning for Whole Slide Pathology Diagnosis
Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner
Cause-Effect Driven Optimization for Robust Medical Visual Question Answering with Language Biases
RegionMatch: Pixel-Region Collaboration for Semi-Supervised Semantic Segmentation in Remote Sensing Images
CFII-Net: Explicit Class Embeddings and Feature Maps Through Iterative Interaction for Boosting Medical Image Segmentation
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming Problems
Large-Scale Trade-Off Curve Computation for Incentive Allocation with Cardinality and Matroid Constraints
Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation
Verified Certificates via SAT and Computer Algebra Systems for the Ramsey R(3,8) and R(3,9) Problems
Guiding Large Language Models in Modeling Optimization Problems via Question Partitioning
New Sequence-Independent Lifting Techniques for Cover Inequalities and When They Induce Facets
Empowering Multimodal Road Traffic Profiling with Vision Language Models and Frequency Spectrum Fusion
Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding
FCKT: Fine-Grained Cross-Task Knowledge Transfer with Semantic Contrastive Learning for Targeted Sentiment Analysis
A Novel Sparse Active Online Learning Framework for Fast and Accurate Streaming Anomaly Detection Over Data Streams
SourceDetMamba: A Graph-aware State Space Model for Source Detection in Sequential Hypergraphs
HyperDet: Source Detection in Hypergraphs via Interactive Relationship Construction and Feature-rich Attention Fusion
Suit the Node Pair to the Case: A Multi-Scale Node Pair Grouping Strategy for Graph-MLP Distillation
Picturized and Recited with Dialects: A Multimodal Chinese Representation Framework for Sentiment Analysis of Classical Chinese Poetry
Exploiting Self-Refining Normal Graph Structures for Robust Defense against Unsupervised Adversarial Attacks
Unsupervised Feature Transformation via In-context Generation, Generator-critic LLM Agents, and Duet-play Teaming
NeuBM: Mitigating Model Bias in Graph Neural Networks Through Neutral Input Calibration
Enabling Visual Foundation Models to Teach Compact Students via Mixture of Distillation
NAAST-GNN: Neighborhood Adaptive Aggregation and Spectral Tuning for Graph Anomaly Detection
Efficient Inter-Operator Scheduling for Concurrent Recommendation Model Inference on GPU
Balancing Imbalance: Data-Scarce Urban Flow Prediction via Spatio-Temporal Balanced Transfer Learning
HPDM: A Hierarchical Popularity-aware Debiased Modeling Approach for Personalized News Recommender
MaskDGNN: Self-Supervised Dynamic Graph Neural Networks with Activeness-aware Temporal Masking
A Generalized Diffusion Framework with Learnable Propagation Dynamics for Source Localization
Good Advisor for Source Localization: Using Large Language Model to Guide the Source Inference Process
Interaction-Data-guided Conditional Instrumental Variables for Debiasing Recommender Systems
Hybrid Relational Graphs with Sentiment-laden Semantic Alignment for Multimodal Emotion Recognition in Conversation
FedCCH: Automatic Personalized Graph Federated Learning for Inter-Client and Intra-Client Heterogeneity
A Dynamic Knowledge Update-Driven Model with Large Language Models for Fake News Detection
Balancing User-Item Structure and Interaction with Large Language Models and Optimal Transport for Multimedia Recommendation
Representation Learning with Mutual Influence of Modalities for Node Classification in Multi-Modal Heterogeneous Networks
TOTF: Missing-Aware Encoders for Clustering on Multi-View Incomplete Attributed Graphs
Beyond Individual and Point: Next POI Recommendation via Region-aware Dynamic Hypergraph with Dual-level Modeling
Variational Graph Auto-Encoder Driven Graph Enhancement for Sequential Recommendation
CLLMRec: Contrastive Learning with LLMs-based View Augmentation for Sequential Recommendation
Dynamic Seed-GrowthCM: A Dynamic Benefit-Oriented Algorithm for Core Maximization on Large Graphs
Causal Learning Meet Covariates: Empowering Lightweight and Effective Nationwide Air Quality Forecasting
STLSP: Integrating Structure and Text with Large Language Models for Link Sign Prediction of Networks
AI Ethics, Trust, Fairness
MMNet: Missing-Aware and Memory-Enhanced Network for Multivariate Time Series Imputation
Exploring the Over-smoothing Problem of Graph Neural Networks for Graph Classification: An Entropy-based Viewpoint
HA-SCN: Learning Hierarchical Aligned Subtree Convolutional Networks for Graph Classification
Unveiling the Power of Noise Priors: Enhancing Diffusion Models for Mobile Traffic Prediction
Multi-Scale Temporal Neural Network for Stock Trend Prediction Enhanced by Temporal Hyepredge Learning
Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning
Towards Recognizing Spatial-temporal Collaboration of EEG Phase Brain Networks for Emotion Understanding
Trace: Structural Riemannian Bridge Matching for Transferable Source Localization in Information Propagation
Riding the Wave: Multi-Scale Spatial-Temporal Graph Learning for Highway Traffic Flow Prediction Under Overload Scenarios
SEP: A General Lossless Compression Framework with Semantics Enhancement and Multi-Stream Pipelines
Distribution-Aware Online Learning for Urban Spatiotemporal Forecasting on Streaming Data
RePST: Language Model Empowered Spatio-Temporal Forecasting via Semantic-Oriented Reprogramming
An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks
EVICheck: Evidence-Driven Independent Reasoning and Combined Verification Method for Fact-Checking
FedHAN: A Cache-Based Semi-Asynchronous Federated Learning Framework Defending Against Poisoning Attacks in Heterogeneous Clients
Learning Neural Jump Stochastic Differential Equations with Latent Graph for Multivariate Temporal Point Processes
Exploiting Text Semantics for Few and Zero Shot Node Classification on Text-attributed Graph
Let’s Group: A Plug-and-Play SubGraph Learning Method for Memory-Efficient Spatio-Temporal Graph Modeling
Where and When: Predict Next POI and Its Explicit Timestamp in Sequential Recommendation
DGraFormer: Dynamic Graph Learning Guided Multi-Scale Transformer for Multivariate Time Series Forecasting
Towards Equilibrium: An Instantaneous Probe-and-Rebalance Multimodal Learning Approach
AdaMixT: Adaptive Weighted Mixture of Multi-Scale Expert Transformers for Time Series Forecasting
GCTAM: Global and Contextual Truncated Affinity Combined Maximization Model For Unsupervised Graph Anomaly Detection
MEGAD: A Memory-Efficient Framework for Large-Scale Attributed Graph Anomaly Detection
Time-Frequency Disentanglement Boosted Pre-Training: A Universal Spatio-Temporal Modeling Framework
An End-to-End Simple Clustering Hierarchical Pooling Operation for Graph Learning Based on Top-K Node Selection
CoLA-Former: Graph Transformer Using Communal Linear Attention for Lightweight Sequential Recommendation
TrajCogn: Leveraging LLMs for Cognizing Movement Patterns and Travel Purposes from Trajectories
Progressive Prefix-Memory Tuning for Complex Logical Query Answering on Knowledge Graphs
Cap-and-Penalize: Competitive Mechanisms for Multi-Phase Regularized Online Allocation
Settling the Complexity of Popularity in Additively Separable and Fractional Hedonic Games
Public Signaling in Markets with Information Asymmetry Using a Limited Number of Signals
Credit Assignment and Fine-Tuning Enhanced Reinforcement Learning for Collaborative Spatial Crowdsourcing
ListenNet: A Lightweight Spatio-Temporal Enhancement Nested Network for Auditory Attention Detection
Constrained Preferential Bayesian Optimization and Its Application in Banner Ad Design
Adaptive Gradient Learning for Spiking Neural Networks by Exploiting Membrane Potential Dynamics
ST-USleepNet: A Spatial-Temporal Coupling Prominence Network for Multi-Channel Sleep Staging
ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks
ID-RemovalNet: Identity Removal Network for EEG Privacy Protection with Enhancing Decoding Tasks
Do Mentioned Items Truly Matter? Enhancing Conversational Recommender Systems with Causal Intervention and Large Language Models
HLMTrans: A Sim-to-Real Transfer Framework for Spatial Crowdsourcing with Human-Guided Language Models
A Cross-Modal Densely Guided Knowledge Distillation Based on Modality Rebalancing Strategy for Enhanced Unimodal Emotion Recognition
ActiveHAI: Active Collection Based Human-AI Diagnosis with Limited Expert Predictions
Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting
Counterfactual Explanations Under Model Multiplicity and Their Use in Computational Argumentation
Integrating Answer Set Programming and Large Language Models for Enhanced Structured Representation of Complex Knowledge in Natural Language
A General Framework for Representing Controlled Natural Language Sentences and Translation to KR Formalisms
Assessing the Exposure to Public Knowledge in Policy-Protected Description Logic Ontologies
A Logic-based Framework for Decoding Enthymemes in Argument Maps Involving Implicitness in Premises and Claims
Human-Readable Neuro-Fuzzy Networks from Frequent Yet Discernible Patterns in Reward-Based Environments
Approximation Fixpoint Theory as a Unifying Framework for Fuzzy Logic Programming Semantics
A Fine-Grained Complexity View on Propositional Abduction - Algorithms and Lower Bounds
Improving Efficiency of Answer Set Planning with Rough Solutions from Large Language Models for Robotic Task Planning
Instantiation-based Formalization of Logical Reasoning Tasks Using Language Models and Logical Solvers
FGeo-HyperGNet: Geometric Problem Solving Integrating FormalGeo Symbolic System and Hypergraph Neural Network
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning
Adversarial Training for Graph Convolutional Networks: Stability and Generalization Analysis
Where Does This Data Come From? Enhanced Source Inference Attacks in Federated Learning
Learning to Extrapolate and Adjust: Two-Stage Meta-Learning for Concept Drift in Online Time Series Forecasting
DO-CoLM: Dynamic 3D Conformation Relationships Capture with Self-Adaptive Ordering Molecular Relational Modeling in Language Models
A Hybrid Multi-Factor Network with Dynamic Sequence Modeling for Early Warning of Intraoperative Hypotension
GRAPE: Heterogeneous Graph Representation Learning for Genetic Perturbation with Coding and Non-Coding Biotype
SPoRt - Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RL
A Fast Neural Architecture Search Method for Multi-Modal Classification via Knowledge Sharing
FedDLAD: A Federated Learning Dual-Layer Anomaly Detection Framework for Enhancing Resilience Against Backdoor Attacks
Screening, Rectifying, and Re-Screening: A Unified Framework for Tuning Vision-Language Models with Noisy Labels
Optimal Transport on Categorical Data for Conterfactuals Using Compositional Data and Dirichlet Transport
Learn from Global Rather Than Local: Consistent Context-Aware Representation Learning for Multi-View Graph Clustering
Structure-Aware Handwritten Text Recognition via Graph-Enhanced Cross-Modal Mutual Learning
Graph Random Walk with Feature-Label Space Alignment: A Multi-Label Feature Selection Method
Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning
LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data
Disentangling Multi-view Representations via Curriculum Learning with Learnable Prior
Integrating Independent Layer-Wise Rank Selection with Low-Rank SVD Training for Model Compression: A Theory-Driven Approach
Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning
Incentivizing Safer Actions in Policy Optimization for Constrained Reinforcement Learning
Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space
FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
Model-Based Closed-Loop Control Algorithm for Stochastic Partial Differential Equation Control
FedBG: Proactively Mitigating Bias in Cross-Domain Graph Federated Learning Using Background Data
Visual Perturbation and Adaptive Hard Negative Contrastive Learning for Compositional Reasoning in Vision-Language Models
Learning to Explain: Towards Human-Aligned Explainability in Deep Reinforcement Learning via Attention Guidance
FedCPD:Personalized Federated Learning with Prototype-Enhanced Representation and Memory Distillation
A Multi-view Fusion Approach for Enhancing Speech Signals via Short-time Fractional Fourier Transform
Where and How to Enhance: Discovering Bit-Width Contribution for Mixed Precision Quantization
CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series Forecasting
CSAHFL:Clustered Semi-Asynchronous Hierarchical Federated Learning for Dual-layer Non-IID in Heterogeneous Edge Computing Networks
MiniMal: Hard-Label Adversarial Attack Against Static Malware Detection with Minimal Perturbation
Leveraging Peer-Informed Label Consistency for Robust Graph Neural Networks with Noisy Labels
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning
FAST: A Lightweight Mechanism Unleashing Arbitrary Client Participation in Federated Learning
RepObE: Representation Learning-Enhanced Obfuscation Encryption Modular Semantic Task Framework
Trajectory-Dependent Generalization Bounds for Pairwise Learning with φ-mixing Samples
CFDONEval: A Comprehensive Evaluation of Operator-Learning Neural Network Models for Computational Fluid Dynamics
RTdetector: Deep Transformer Networks for Time Series Anomaly Detection Based on Reconstruction Trend
Enhancing Semantic Clarity: Discriminative and Fine-grained Information Mining for Remote Sensing Image-Text Retrieval
A Fast-Adaptive Cognitive Diagnosis Framework for Computerized Adaptive Testing Systems
A Neuro-Symbolic Framework for Sequence Classification with Relational and Temporal Knowledge
Multi-Omics Analysis for Cancer Subtype Inference via Unrolling Graph Smoothness Priors
Prototype-guided Knowledge Propagation with Adaptive Learning for Lifelong Person Re-identification
Capturing Individuality and Commonality Between Anchor Graphs for Multi-View Clustering
RLBCD: Residual-guided Latent Brownian-bridge Co-Diffusion for Anatomical-to-Metabolic Image Synthesis
MCF-Spouse: A Multi-Label Causal Feature Selection Method with Optimal Spouses Discovery
Consistency-Aware Padding for Incomplete Multi-Modal Alignment Clustering Based on Self-Repellent Greedy Anchor Search
Mitigating Over-Smoothing in Graph Neural Networks via Separation Coefficient-Guided Adaptive Graph Structure Adjustment
S-EPOA: Overcoming the Indistinguishability of Segments with Skill-Driven Preference-Based Reinforcement Learning
Robult: Leveraging Redundancy and Modality-Specific Features for Robust Multimodal Learning
Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach
LLM-TPF: Multiscale Temporal Periodicity-Semantic Fusion LLMs for Time Series Forecasting
Dynamic Higher-Order Relations and Event-Driven Temporal Modeling for Stock Price Forecasting
Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization
Breaking the Self-Evaluation Barrier: Reinforced Neuro-Symbolic Planning with Large Language Models
QuantileFormer: Probabilistic Time Series Forecasting with a Pattern-Mixture Decomposed VAE Transformer
MATCH: Modality-Calibrated Hypergraph Fusion Network for Conversational Emotion Recognition
GSDNet: Revisiting Incomplete Multimodality-Diffusion Emotion Recognition from the Perspective of Graph Spectrum
Metapath and Hypergraph Structure-based Multi-Channel Graph Contrastive Learning for Student Performance Prediction
RotateKV: Accurate and Robust 2-Bit KV Cache Quantization for LLMs via Outlier-Aware Adaptive Rotations
Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data
Connecting Giants: Synergistic Knowledge Transfer of Large Multimodal Models for Few-Shot Learning
InstGAN: Instant Actor-Critic-Driven GAN for De Novo Molecule Generation and Property Optimization
Enhancing Transferability of Audio Adversarial Example for Both Frequency- and Time-domain
A Symmetric Relative-Error Loss Function for Intermittent Multiscale Signal Modelling
Diffuse&Refine: Intrinsic Knowledge Generation and Aggregation for Incremental Object Detection
Dynamic Multiple High-order Correlations Fusion with Noise Filtering for Incomplete Multi-view Noisy-label Learning
From Individual to Universal: Regularized Multi-view Joint Representation for Multi-view Subspace-Preserving Recovery
DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation
FedCM: Client Clustering and Migration in Federated Learning via Gradient Path Similarity and Update Direction Deviation
MASTER: A Multi-granularity Invariant Structure Clustering Scheme for Multi-view Clustering
Learn Multi-task Anchor: Joint View Imputation and Label Generation for Incomplete Multi-view Clustering
All Roads Lead to Rome: Exploring Edge Distribution Shifts for Heterophilic Graph Learning
BILE: An Effective Behavior-based Latent Exploration Scheme for Deep Reinforcement Learning
Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks
From End-to-end to Step-by-step: Learning to Abstract via Abductive Reinforcement Learning
SCNNs: Spike-based Coupling Neural Networks for Understanding Structural-Functional Relationships in the Human Brain
Fast Second-Order Online Kernel Learning Through Incremental Matrix Sketching and Decomposition
Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain
Zero-shot Federated Unlearning via Transforming from Data-Dependent to Personalized Model-Centric
Boosting Few-Shot Open-Set Object Detection via Prompt Learning and Robust Decision Boundary
Divide and Conquer: Coordinating Multiplex Mixture of Graph Learners to Handle Multi-Omics Analysis
LRGR: Self-Supervised Incomplete Multi-View Clustering via Local Refinement and Global Realignment
Computer Vision
Spatially Resolved Transcriptomics Data Clustering with Tailored Spatial-scale Modulation
DaringFed: A Dynamic Bayesian Persuasion Pricing for Online Federated Learning Under Two-sided Incomplete Information
Beyond Statistical Analysis: Multimodal Framework for Time Series Forecasting with LLM-Driven Temporal Pattern
A Priori Estimation of the Approximation, Optimization and Generalization Errors of Random Neural Networks for Solving Partial Differential Equations
No Regret Reinforcement Learning Algorithms for Online Scheduling with Multi-Stage Tasks
Problem-dependent Regret for Lexicographic Multi-Armed Bandits with Adversarial Corruptions
Empowering Vision Transformers with Multi-Scale Causal Intervention for Long-Tailed Image Classification
Decoupling and Reconstructing: A Multimodal Sentiment Analysis Framework Towards Robustness
From General Relation Patterns to Task-Specific Decision-Making in Continual Multi-Agent Coordination
Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization
M4Bench: A Benchmark of Multi-domain Multi-granularity Multi-image Understanding for Multi-modal Large Language Models
ExpertDiff: Head-less Model Reprogramming with Diffusion Classifiers for Out-of-Distribution Generalization
Explaining Black-box Model Predictions via Two-level Nested Feature Attributions with Consistency Property
FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization
A Multi-Granularity Clustering Approach for Federated Backdoor Defense with the Adam Optimizer
Collaborative Multi-LoRA Experts with Achievement-based Multi-Tasks Loss for Unified Multimodal Information Extraction
Deduction with Induction: Combining Knowledge Discovery and Reasoning for Interpretable Deep Reinforcement Learning
Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecasting
QiMeng-TensorOp: One-Line Prompt is Enough for High-Performance Tensor Operator Generation with Hardware Primitives
AdaptPFL: Unlocking Cross-Device Palmprint Recognition via Adaptive Personalized Federated Learning with Feature Decoupling
DM-POSA: Enhancing Open-World Test-Time Adaptation with Dual-Mode Matching and Prompt-Based Open Set Adaptation
Instance Relation Learning Network with Label Knowledge Propagation for Few-shot Multi-label Intent Detection
High-Confident Local Structure Guided Consensus Graph Learning For Incomplete Multi-view Clustering
A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting
Enhancing the Performance of Global Model by Improving the Adaptability of Local Models in Federated Learning
Dyn-D^2P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee
Strategy-Architecture Synergy: A Multi-View Graph Contrastive Paradigm for Consistent Representations
Logic Distillation: Learning from Code Function by Function for Decision-making Tasks
TSTAI: A Time-varying Brain Effective Connectivity Network Construction Method Combining with Brain Active Information
Minimizing Polarization and Disagreement in the Friedkin–Johnsen Model with Unknown Innate Opinions
State Feedback Enhanced Graph Differential Equations for Multivariate Time Series Forecasting
Advancing Community Detection with Graph Convolutional Neural Networks: Bridging Topological and Attributive Cohesion
Conditional Causal Representation Learning for Heterogeneous Single-cell RNA Data Integration and Prediction
Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge Transfer
CompLex: Music Theory Lexicon Constructed by Autonomous Agents for Automatic Music Generation
APIMig: A Project-Level Cross-Multi-Version API Migration Framework Based on Evolution Knowledge Graph
Secure and Efficient Watermarking for Latent Diffusion Models in Model Distribution Scenarios
DASS: A Dual-Branch Attention-based Framework for Trajectory Similarity Learning with Spatial and Semantic Fusion
RetroMoE: A Mixture-of-Experts Latent Translation Framework for Single-step Retrosynthesis
MTGIB-UNet: A Multi-Task Graph Information Bottleneck and Uncertainty Weighted Network for ADMET Prediction
KnowMDD: Knowledge-guided Cross Contrastive Learning for Major Depressive Disorder Diagnosis
PAMol: Pocket-Aware Drug Design Method with Hypergraph Representation of Protein Pocket Structure and Feature Fusion
Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning
Towards Generalizable Neural Simulators: Addressing Distribution Shifts Induced by Environmental and Temporal Variations
Enhancing Multimodal Protein Function Prediction Through Dual-Branch Dynamic Selection with Reconstructive Pre-Training
MA-RAG: Automating Role Engineering for RESTful APIs with Multi-Head Attention and Retrieval-Augmented Generation
Localizing Before Answering: A Benchmark for Grounded Medical Visual Question Answering
Think Twice Before Adaptation: Improving Adaptability of DeepFake Detection via Online Test-Time Adaptation
Solving Copyright Infringement on Short Video Platforms: Novel Datasets and an Audio Restoration Deep Learning Pipeline
Disentangled and Personalized Representation Learning for Next Point-of-Interest Recommendation
PDDFormer: Pairwise Distance Distribution Graph Transformer for Crystal Material Property Prediction
LogiCase: Effective Test Case Generation from Logical Description in Competitive Programming
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems
Image-Enhanced Hybrid Encoding with Reinforced Contrastive Learning for Spatial Domain Identification in Spatial Transcriptomics
ST-TAR: An Efficient Spatio-Temporal Learning Framework for Traffic Accident Risk Forecasting
TESTN: A Triad-Enhanced Spatio-Temporal Network for Multi-Temporal POI Relationship Inference
Incorporating Legal Logic into Deep Learning: An Intelligent Approach to Probation Prediction
POMP: Pathology-omics Multimodal Pre-training Framework for Cancer Survival Prediction
Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models
scSiameseClu: A Siamese Clustering Framework for Interpreting Single-cell RNA Sequencing Data
Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networks
MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning
Category-aware EEG Image Generation Based on Wavelet Transform and Contrast Semantic Loss
Subgraph Information Bottleneck with Causal Dependency for Stable Molecular Relational Learning
Multimodal Inverse Attention Network with Intrinsic Discriminant Feature Exploitation for Fake News Detection
MMGIA: Gradient Inversion Attack Against Multimodal Federated Learning via Intermodal Correlation
Enhancing Nighttime Semantic Segmentation with Visual-Linguistic Priors and Wavelet Transform
DiffECG: Diffusion Model-Powered Label-Efficient and Personalized Arrhythmia Diagnosis
Scalable Multi-Stage Influence Function for Large Language Models via Eigenvalue-Corrected Kronecker-Factored Parameterization
M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction
SecV: LLM-based Secure Verilog Generation with Clue-Guided Exploration on Hardware-CWE Knowledge Graph
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training
Improving Prediction Certainty Estimation for Reliable Early Exiting via Null Space Projection
How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback
Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant
Multi-modal Anchor Gated Transformer with Knowledge Distillation for Emotion Recognition in Conversation
Can Retelling Have Adequate Information for Reasoning? An Enhancement Method for Imperfect Video Understanding with Large Language Model
Variational Multi-Modal Hypergraph Attention Network for Multi-Modal Relation Extraction
Multimodal Knowledge Retrieval-Augmented Iterative Alignment for Satellite Commonsense Conversation
Can Large Models Teach Student Models to Solve Mathematical Problems Like Human Beings? A Reasoning Distillation Method via Multi-LoRA Interaction
KnowRA: Knowledge Retrieval Augmented Method for Document-level Relation Extraction with Comprehensive Reasoning Abilities
Accurate Sublayer Pruning for Large Language Models by Exploiting Latency and Tunability Information
R2DQG: A Quality Meets Diversity Framework for Question Generation over Knowledge Bases
DFMU: Distribution-based Framework for Modeling Aleatoric Uncertainty in Multimodal Sentiment Analysis
Improving Consistency Identification in Task-oriented Dialogue Through Multi-Agent Collaboration
MPPQ: Enhancing Post-Training Quantization for LLMs via Mixed Supervision, Proxy Rounding, and Pre-Searching
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework
Unveiling Maternity and Infant Care Conversations: A Chinese Dialogue Dataset for Enhanced Parenting Support
ARPDL: Adaptive Relational Prior Distribution Loss as an Adapter for Document-Level Relation Extraction
D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning
Detecting Hallucination in Large Language Models Through Deep Internal Representation Analysis
Sentiment-enhanced Multi-hop Connected Graph Attention Network for Multimodal Aspect-Based Sentiment Analysis
Multi-Label Text Classification with Label Attention Aware and Correlation Aware Contrastive Learning
Handling Infinite Domain Parameters in Planning Through Best-First Search with Delayed Partial Expansions
Optimal Planning to Coordinate Science Data Collection and Downlink for a Constellation of Agile Satellites with Limited Storage
Semi-Clairvoyant Scheduling of Speculative Decoding Requests to Minimize LLM Inference Latency
RobustHAR: Multi-scale Spatial-temporal Masked Self-supervised Pre-training for Robust Human Activity Recognition
GATES: Cost-aware Dynamic Workflow Scheduling via Graph Attention Networks and Evolution Strategy
DGL: Dynamic Global-Local Information Aggregation for Scalable VRP Generalization with Self-Improvement Learning
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
Computational Complexity of Planning for Recursive Primitive Task Networks: Selective Action Nullification with State Preservation
Tree-of-AdEditor: Heuristic Tree Reasoning for Automated Video Advertisement Editing with Large Language Model
State Revisit and Re-explore: Bridging Sim-to-Real Gaps in Offline-and-Online Reinforcement Learning with An Imperfect Simulator
Risk-Aware Task Migration for Multiplex Unmanned Swarm Networks in Adversarial Environments
GCNT: Graph-Based Transformer Policies for Morphology-Agnostic Reinforcement Learning
Beyond the Map: Learning to Navigate Unseen Urban Dynamics Using Diffusion-Guided Deep Reinforcement Learning
Understanding Matters: Semantic-Structural Determined Visual Relocalization for Large Scenes
Code-BT: A Code-Driven Approach to Behavior Tree Generation for Robot Tasks Planning with Large Language Models
DiffSQL: Leveraging Diffusion Model for Zero-Shot Self-Supervised Monocular Depth Estimation
Speeding Up Hyper-Heuristics With Markov-Chain Operator Selection and the Only-Worsening Acceptance Operator
Theoretical Analysis of Evolutionary Algorithms with Quality Diversity for a Classical Path Planning Problem
The First Theoretical Approximation Guarantees for the Non-Dominated Sorting Genetic Algorithm III (NSGA-III)
Tight Runtime Guarantees From Understanding the Population Dynamics of the GSEMO Multi-Objective Evolutionary Algorithm
Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback
A First Runtime Analysis of NSGA-III on a Many-Objective Multimodal Problem: Provable Exponential Speedup via Stochastic Population Update
A Theoretical Perspective on Why Stochastic Population Update Needs an Archive in Evolutionary Multi-objective Optimization
X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning
Set-Based Retrograde Analysis: Precomputing the Solution to 28-card Bridge Double Dummy Deals
InfVC: An Inference-Enhanced Local Search Algorithm for the Minimum Vertex Cover Problem in Massive Graphs
Bidirectional Search while Ensuring Meet-In-The-Middle via Effective and Efficient-to-Compute Termination Conditions
Inferring Causal Protein Signaling Networks with Reinforcement Learning via Artificial Bee Colony Neural Architecture Search
Attractor-based Closed List Search: Sparsifying the Closed List for Efficient Memory-Constrained Planning
Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders
Efficient Constraint-based Window Causal Graph Discovery in Time Series with Multiple Time Lags
Conditional Independent Test in the Presence of Measurement Error with Causal Structure Learning
SpeechHGT: A Multimodal Hypergraph Transformer for Speech-Based Early Alzheimer’s Disease Detection
RF-DTR: A Multi-Stage DCT Token Regression Network for Progressive Rib Fracture Mask Refinement
Rethinking Remaining Useful Life Prediction with Scarce Time Series Data: Regression Under Indirect Supervision
Hallucination Reduction in Video-Language Models via Hierarchical Multimodal Consistency
Optimize Battery Control: A Multi-Objective Evolutionary Ensemble Reinforcement Learning Approach
DeepFeatIoT: Unifying Deep Learned, Randomized, and LLM Features for Enhanced IoT Time Series Sensor Data Classification in Smart Industries
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data
Empowering Quantum Serverless Circuit Deployment Optimization via Graph Contrastive Learning and Learning-to-Rank Co-designed Approaches
Optimizing the Battery-Swapping Problem in Urban E-Bike Systems with Reinforcement Learning
TCCD: Tree-guided Continuous Causal Discovery via Collaborative MCTS-Parameter Optimization
CycSeq: Leveraging Cyclic Data Generation for Accurate Perturbation Prediction in Single-Cell RNA-Seq
CogTwin: A Hybrid Cognitive Architecture Framework for Adaptable and Cognitive Digital Twins
The Graph’s Apprentice: Teaching an LLM Low-Level Knowledge for Circuit Quality Estimation
MolHFCNet: Enhancing Molecular Graph Representations with Hierarchical Feature Combining and Hybrid Pretraining
NSF-MAP: Neurosymbolic Multimodal Fusion for Robust and Interpretable Anomaly Prediction in Assembly Pipelines
COLUR: Confidence-Oriented Learning, Unlearning and Relearning with Noisy-Label Data for Model Restoration and Refinement
Map2Traj: Street Map Piloted Zero-shot Trajectory Generation Method for Wireless Network Optimization
DeCo: Defect-Aware Modeling with Contrasting Matching for Optimizing Task Assignment in Online IC Testing
Physics-based Generative Models for Geometrically Consistent and Interpretable Wireless Channel Synthesis
Learning Dynamical Coupled Operator For High-dimensional Black-box Partial Differential Equations
SpaceDet: A Large-scale Space-based Image Dataset and RSO Detection for Space Situational Awareness
Multi-Hierarchical Fine-Grained Feature Mapping Driven by Feature Contributions for Molecular Odor Prediction
Generating Grounded Responses to Counter Misinformation via Learning Efficient Fine-Grained Critiques
KGCL: Knowledge-Enhanced Graph Contrastive Learning for Retrosynthesis Prediction Based on Molecular Graph Editing
Generative Co-Design of Antibody Sequences and Structures via Black-Box Guidance in a Shared Latent Space
Enhancing Portfolio Optimization via Heuristic-Guided Inverse Reinforcement Learning with Multi-Objective Reward and Graph-based Policy Learning
FLARE: A Framework for Stellar Flare Forecasting Using Stellar Physical Properties and Historical Records
Faster Annotation for Elevation-Guided Flood Extent Mapping by Consistency-Enhanced Active Learning
Agent-based Modeling Meets the Capability Approach for Human Development: Simulating Homelessness Policy-making
SHIELD: A Self-supervised, Silicosis-focused Hierarchical Imaging Framework for Occupational Lung Disease Diagnosis
MutationGuard: A Graph and Temporal-Spatial Neural Method for Detecting Mutation Telecommunication Fraud
An Interactive Game-based Multi-Agent AI System for Children’s Social and Emotional Development
Recommender Systems for Democracy: Toward Adversarial Robustness in Voting Advice Applications
Exploring Equity of Climate Policies Using Multi-Agent Multi-Objective Reinforcement Learning
LogiDebrief: A Signal-Temporal Logic Based Automated Debriefing Approach with Large Language Models Integration
Detection and Geographic Localization of Natural Objects in the Wild: A Case Study on Palms
Deconfounding Multi-Cause Latent Confounders: A Factor-Model Approach to Climate Model Bias Correction
Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs
Weather Foundation Model Enhanced Decentralized Photovoltaic Power Forecasting Through Spatio-temporal Knowledge Distillation
Direct Estimation of Attenuation Information from Sinograms for Positron Emission Tomography Reconstruction
IGraSS: Learning to Identify Infrastructure Networks from Satellite Imagery by Iterative Graph-constrained Semantic Segmentation
Computer Vision
An Ethical Dataset from Real-World Interactions Between Users and Large Language Models
What is Behind Homelessness Bias? Using LLMs and NLP to Mitigate Homelessness by Acting on Social Stigma
Leveraging Artificial Intelligence to Bridge Gaps in Pediatric Oncology Care for Marginalized Spanish-Speaking Communities
Towards the 30 by 30 Kunming-Montreal Global Biodiversity Framework Target: Optimising Graph Connectivity in Constraint-Based Spatial Planning
AI-Assisted Triage and Decision Support of Head and Neck Cancer Screening and Diagnosis in Low-Resourced Settings
Deep Reinforcement Learning for Efficient and Fair Allocation of Healthcare Resources
Mat-Instructions: A Large-Scale Inorganic Material Instruction Dataset for Large Language Models
Expanding Connected Components from Alternative Terminals: Global Optimization for Freshwater Fishes Under the UN's 30x30 Conservation Goal
Hazard Function Guided Agent-Based Models: A Case Study of Return Migration from Poland to Ukraine
SMILE: A Scale-aware Multiple Instance Learning Method for Multicenter STAS Lung Cancer Histopathology Diagnosis
CoDiCast: Conditional Diffusion Model for Global Weather Forecasting with Uncertainty Quantification
SAHAY: Multimodal, Privacy-Preserving AI for Suicide Risk Detection and Intervention in India
AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems
Enhancing Online Climate Discourse: A Two-Stage Framework for Climate Content Categorization and Moderation
DECASTE: Unveiling Caste Stereotypes in Large Language Models Through Multi-Dimensional Bias Analysis
MCloudNet: An Ultra-Short-Term Photovoltaic Power Forecasting Framework With Multi-Layer Cloud Coverage
Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction
ContextAware: A Multi-Agent Framework for Detecting Harmful Image-Based Comments on Social Media
City-Level Foreign Direct Investment Prediction with Tabular Learning on Judicial Data
Exploring Multimodal Foundation AI and Expert-in-the-Loop for Sustainable Management of Wild Salmon Fisheries in Indigenous Rivers
LLM-based Collaborative Agents with Pedagogy-guided Interaction Modeling for Timely Instructive Feedback Generation in Task-oriented Group Discussions
QBR – A Question-Bank-Based Approach to Fine-Grained Legal Knowledge Retrieval for the General Public
OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data
BGM: Demand Prediction for Expanding Bike-Sharing Systems with Dynamic Graph Modeling
Reinforcement Learning for Hybrid Charging Stations Planning and Operation Considering Fixed and Mobile Chargers
Bidirectional Human–AI Collaboration for Equitable Student Performance Prediction via Deep Uncertainty Learning
A³-Net: Calibration-Free Multi-View 3D Hand Reconstruction for Enhanced Musical Instrument Learning
FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance
Scan-and-Print: Patch-level Data Summarization and Augmentation for Content-aware Layout Generation in Poster Design
SmartSpatial: Enhancing 3D Spatial Awareness in Stable Diffusion with a Novel Evaluation Framework
Precarity and Solidarity: Preliminary Results on a Study of Queer and Disabled Fiction Writers’ Experiences with Generative AI
METEOR: Melody-aware Texture-controllable Symbolic Music Re-Orchestration via Transformer VAE
GETMusic: Generating Music Tracks with a Unified Representation and Diffusion Framework
Towards a Practical Tool for Music Composition: Using Constraint Programming to Model Chord Progressions and Modulations
AdaptEdit: An Adaptive Correspondence Guidance Framework for Reference-Based Video Editing
A Picture is Worth a Thousand Prompts? Efficacy of Iterative Human-Driven Prompt Refinement in Image Regeneration Tasks
NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms
MagicTailor: Component-Controllable Personalization in Text-to-Image Diffusion Models
Weakly-Supervised Movie Trailer Generation Driven by Multi-Modal Semantic Consistency
Creative Momentum Transfer: How Timing and Labeling of AI Suggestions Shape Iterative Human Ideation
HCRide: Harmonizing Passenger Fairness and Driver Preference for Human-Centered Ride-Hailing
Shaping Shared Languages: Human and Large Language Models' Inductive Biases in Emergent Communication
LivePoem: Improving the Learning Experience of Classical Chinese Poetry with AI-Generated Musical Storyboards
The Delta of Thought: Channeling Rivers of Commonsense Knowledge in the Sea of Metaphorical Interpretations
Toward Informed AV Decision-Making: Computational Model of Well-being and Trust in Mobility
Enhancing Automated Grading in Science Education through LLM-Driven Causal Reasoning and Multimodal Analysis
Neuro-Symbolic Artificial Intelligence: A Task-Directed Survey in the Black-Box Models Era
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction To Generation and Beyond
A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities
A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics
Image Captioning Evaluation in the Age of Multimodal LLMs: Challenges and Future Perspectives
A Comprehensive and Systematic Review for Deep Learning-Based De Novo Peptide Sequencing
Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models
A Survey on Multi-View Knowledge Graph: Generation, Fusion, Applications and Future Directions
Grounding Open-Domain Knowledge from LLMs to Real-World Reinforcement Learning Tasks: A Survey
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors (Extended Abstract)
FairCognizer: A Model for Accurate Predictions with Inherent Fairness Evaluation (Extended Abstract)
Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection (Extended Abstract)
Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring (Extended Abstract)
SEE: Spherical Embedding Expansion for Improving Deep Metric Learning (Extended Abstract)
A Relaxed Symmetric Non-negative Matrix Factorization Approach for Community Discovery (Extended Abstract)
How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debugging (Extended Abstract)
Decoupled Search for the Masses: A Novel Task Transformation for Classical Planning (Extended Abstract)
Credulous Acceptance in High-Order Argumentation Frameworks with Necessities: An Incremental Approach (Abstract Reprint)
Scalable Primal Heuristics Using Graph Neural Networks for Combinatorial Optimization (Abstract Reprint)
The Human in Interactive Machine Learning: Analysis and Perspectives for Ambient Intelligence (Abstract Reprint)
On Measuring Inconsistency in Graph Databases with Regular Path Constraints (Abstract Reprint)
CADS: A Systematic Literature Review on the Challenges of Abstractive Dialogue Summarization (Abstract Reprint)
Confidence-based Estimators for Predictive Performance in Model Monitoring (Abstract Reprint)
CureGraph: Contrastive Multi-Modal Graph Representation Learning for Urban Living Circle Health Profiling and Prediction (Abstract Reprint)
NovPhy: A Physical Reasoning Benchmark for Open-World AI Systems Author Links Open Overlay Panel (Abstract Reprint)
Explain It as Simple as Possible, but No Simpler – Explanation via Model Simplification for Addressing Inferential Gap (Abstract Reprint)
Ensuring Reliable and Transparent Algorithmic Fairness Through Optimal Transport and Uncertainty Quantification
Reward Adaptation via Q-Manipulation: Provably Beneficial Reward Function Transfer in Reinforcement Learning
DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains
Taking STEPS Forward: Enhancing Online Peer-Counseling with Schema Therapy via Socratic Questioning
Combining Code Generating Large Language Models and Self-Play to Iteratively Refine Strategies in Games
TimelyMed: AI-Driven Clinical Course Attribution and Temporal Mapping for Psychiatric Medical Records
Search Swarm: Multiagent Large Language Models Framework for E-commerce Product Search
MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient
TRIKOP: Exploring Visual Prompting Paradigms for Multi-Grade Knee Osteoarthritis Classification on MRI Images
OpenIAI-SNIO: A Systematic AR-Based Assembly Guidance System for Small-Scale, High-Density Industrial Components
HealthLens: A Natural Language Querying System for Interactive Visualization of Electronic Health Records
PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models
Computer Vision
Constraint Satisfaction and Optimization
Data Mining
Game Theory and Economic Paradigms
Humans and AI
Knowledge Representation and Reasoning
Machine Learning
Machine Learning
Machine Learning
Multidisciplinary Topics and Applications
Natural Language Processing
Planning and Scheduling
Robotics
Search
Uncertainty in AI