Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Jeju, Korea
3-9 August 2024Edited by Kate Larson
Sponsored by
International Joint Conferences on Artifical Intelligence (IJCAI)
Published by
International Joint Conferences on Artificial Intelligence
Copyright © 2024 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): 978-1-956792-04-1
Content
Main Track
Agent-based and Multi-agent Systems
Certified Policy Verification and Synthesis for MDPs under Distributional Reach-Avoidance Properties
Truth Table Net: Scalable, Compact & Verifiable Neural Networks with a Dual Convolutional Small Boolean Circuit Networks Form
PTDE: Personalized Training with Distilled Execution for Multi-Agent Reinforcement Learning
Learning Translations: Emergent Communication Pretraining for Cooperative Language Acquisition
Endogenous Energy Reactive Modules Games: Modelling Side Payments among Resource-Bounded Agents
X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learner
Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach
Individual Fairness under Group Fairness Constraints in Bipartite Matching - One Framework to Approximate Them All
Enhancing Cooperation through Selective Interaction and Long-term Experiences in Multi-Agent Reinforcement Learning
Faster Optimal Coalition Structure Generation via Offline Coalition Selection and Graph-Based Search
MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problem
Design a Win-Win Strategy That Is Fair to Both Service Providers and Tasks When Rejection Is Not an Option
ADMN: Agent-Driven Modular Network for Dynamic Parameter Sharing in Cooperative Multi-Agent Reinforcement Learning
AI Ethics, Trust, Fairness
Detecting and Understanding Vulnerabilities in Language Models via Mechanistic Interpretability
Speech-Forensics: Towards Comprehensive Synthetic Speech Dataset Establishment and Analysis
Protecting Object Detection Models from Model Extraction Attack via Feature Space Coverage
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning
By Fair Means or Foul: Quantifying Collusion in a Market Simulation with Deep Reinforcement Learning
Ten Words Only Still Help: Improving Black-Box AI-Generated Text Detection via Proxy-Guided Efficient Re-Sampling
When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers via Membership Inference Attacks
Computer Vision
Attention Shifting to Pursue Optimal Representation for Adapting Multi-granularity Tasks
SGDCL: Semantic-Guided Dynamic Correlation Learning for Explainable Autonomous Driving
Bridging LiDAR Gaps: A Multi-LiDARs Domain Adaptation Dataset for 3D Semantic Segmentation
A Transformer-Based Adaptive Prototype Matching Network for Few-Shot Semantic Segmentation
EVE: Efficient Zero-Shot Text-Based Video Editing With Depth Map Guidance and Temporal Consistency Constraints
Denoising Diffusion-Augmented Hybrid Video Anomaly Detection via Reconstructing Noised Frames
Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors
CF-Deformable DETR: An End-to-End Alignment-Free Model for Weakly Aligned Visible-Infrared Object Detection
Self-Supervised Pre-training with Symmetric Superimposition Modeling for Scene Text Recognition
Enhancing Cross-modal Completion and Alignment for Unsupervised Incomplete Text-to-Image Person Retrieval
TSESNet: Temporal-Spatial Enhanced Breast Tumor Segmentation in DCE-MRI Using Feature Perception and Separability
UniM-OV3D: Uni-Modality Open-Vocabulary 3D Scene Understanding with Fine-Grained Feature Representation
A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder
CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning
Dual Enhancement in ODI Super-Resolution: Adapting Convolution and Upsampling to Projection Distortion
Revealing the Two Sides of Data Augmentation: An Asymmetric Distillation-based Win-Win Solution for Open-Set Recognition
LeMeViT: Efficient Vision Transformer with Learnable Meta Tokens for Remote Sensing Image Interpretation
IntensPure: Attack Intensity-aware Secondary Domain Adaptive Diffusion for Adversarial Purification
Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion
Revitalizing Real Image Deraining via a Generic Paradigm towards Multiple Rainy Patterns
WSRFNet: Wavelet-Based Scale-Specific Recurrent Feedback Network for Diabetic Retinopathy Lesion Segmentation
Cross-modal Generation and Alignment via Attribute-guided Prompt for Unsupervised Text-based Person Retrieval
Advancing Medical Image Segmentation via Self-supervised Instance-adaptive Prototype Learning
Where Elegance Meets Precision: Towards a Compact, Automatic, and Flexible Framework for Multi-modality Image Fusion and Applications
DifTraj: Diffusion Inspired by Intrinsic Intention and Extrinsic Interaction for Multi-Modal Trajectory Prediction
Advancing Generalized Transfer Attack with Initialization Derived Bilevel Optimization and Dynamic Sequence Truncation
C3L: Content Correlated Vision-Language Instruction Tuning Data Generation via Contrastive Learning
FastScene: Text-Driven Fast Indoor 3D Scene Generation via Panoramic Gaussian Splatting
ESP-PCT: Enhanced VR Semantic Performance through Efficient Compression of Temporal and Spatial Redundancies in Point Cloud Transformers
Efficient Screen Content Image Compression via Superpixel-based Content Aggregation and Dynamic Feature Fusion
A Consistency and Integration Model with Adaptive Thresholds for Weakly Supervised Object Localization
CLR-Face: Conditional Latent Refinement for Blind Face Restoration Using Score-Based Diffusion Models
FineFMPL: Fine-grained Feature Mining Prompt Learning for Few-Shot Class Incremental Learning
Expressiveness is Effectiveness: Self-supervised Fashion-aware CLIP for Video-to-Shop Retrieval
Image Retrieval with Self-Supervised Divergence Minimization and Cross-Attention Classification
Explore Internal and External Similarity for Single Image Deraining with Graph Neural Networks
How to Learn Domain-Invariant Representations for Visual Reinforcement Learning: An Information-Theoretical Perspective
Optimal Graph Learning and Nuclear Norm Maximization for Deep Cross-Domain Robust Label Propagation
KTCN: Enhancing Open-World Object Detection with Knowledge Transfer and Class-Awareness Neutralization
Aggregation and Purification: Dual Enhancement Network for Point Cloud Few-shot Segmentation
Beyond Alignment: Blind Video Face Restoration via Parsing-Guided Temporal-Coherent Transformer
Negative Prompt Driven Complementary Parallel Representation for Open-World 3D Object Retrieval
ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition
DFMDA-Net: Dense Fusion and Multi-dimension Aggregation Network for Image Restoration
DTS-TPT: Dual Temporal-Sync Test-time Prompt Tuning for Zero-shot Activity Recognition
Self-Supervised Monocular Depth Estimation in the Dark: Towards Data Distribution Compensation
Fusion from a Distributional Perspective: A Unified Symbiotic Diffusion Framework for Any Multisource Remote Sensing Data Classification
DiffStega: Towards Universal Training-Free Coverless Image Steganography with Diffusion Models
1DFormer: A Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking
Hundredfold Accelerating for Pathological Images Diagnosis and Prognosis through Self-reform Critical Region Focusing
AK4Prompts: Aesthetics-driven Automatically Keywords-Ranking for Prompts in Text-To-Image Models
Detector Collapse: Backdooring Object Detection to Catastrophic Overload or Blindness in the Physical World
Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition
Sparse Multi-Relational Graph Convolutional Network for Multi-type Object Trajectory Prediction
Focus on the Whole Character: Discriminative Character Modeling for Scene Text Recognition
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction Alignment
Class-consistent Contrastive Learning Driven Cross-dimensional Transformer for 3D Medical Image Classification
SceneDiff: Generative Scene-Level Image Retrieval with Text and Sketch Using Diffusion Models
Constraint Satisfaction and Optimization
Knowledge Compilation for Incremental and Checkable Stochastic Boolean Satisfiability
Efficient Cost-Minimization Schemes for Electrical Energy Demand Satisfaction by Prosumers in Microgrids with Battery Storage Capabilities
Bridging the Gap between General and Down-Closed Convex Sets in Submodular Maximization
Enhancing Scalability of Metric Differential Privacy via Secret Dataset Partitioning and Benders Decomposition
Improved Parallel Algorithm for Non-Monotone Submodular Maximization under Knapsack Constraint
A Neural Column Generation Approach to the Vehicle Routing Problem with Two-Dimensional Loading and Last-In-First-Out Constraints
A Multi-Valued Decision Diagram-Based Approach to Constrained Optimal Path Problems over Directed Acyclic Graphs
Data Mining
Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting
DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives
Class-Specific Semantic Generation and Reconstruction Learning for Open Set Recognition
Reconstructing Missing Variables for Multivariate Time Series Forecasting via Conditional Generative Flows
Learning Hierarchy-Enhanced POI Category Representations Using Disentangled Mobility Sequences
Hierarchical Reinforcement Learning on Multi-Channel Hypergraph Neural Network for Course Recommendation
Rethinking the Effectiveness of Graph Classification Datasets in Benchmarks for Assessing GNNs
Enhancing Dual-Target Cross-Domain Recommendation with Federated Privacy-Preserving Learning
KDDC: Knowledge-Driven Disentangled Causal Metric Learning for Pre-Travel Out-of-Town Recommendation
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
Counterfactual User Sequence Synthesis Augmented with Continuous Time Dynamic Preference Modeling for Sequential POI Recommendation
Multi-Relational Graph Attention Network for Social Relationship Inference from Human Mobility Data
Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning
Make Bricks with a Little Straw: Large-Scale Spatio-Temporal Graph Learning with Restricted GPU-Memory Capacity
FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource Allocation
Spatial-Temporal Perceiving: Deciphering User Hierarchical Intent in Session-Based Recommendation
Joint Source Localization in Different Platforms via Implicit Propagation Characteristics of Similar Topics
WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction
Learning Fair Representations for Recommendation via Information Bottleneck Principle
Graph Attention Network with High-Order Neighbor Information Propagation for Social Recommendation
LG-GNN: Local-Global Adaptive Graph Neural Network for Modeling Both Homophily and Heterophily
Sub-Adjacent Transformer: Improving Time Series Anomaly Detection with Reconstruction Error from Sub-Adjacent Neighborhoods
Exploring Urban Semantics: A Multimodal Model for POI Semantic Annotation with Street View Images and Place Names
Score-CDM: Score-Weighted Convolutional Diffusion Model for Multivariate Time Series Imputation
SaSDim:Self-Adaptive Noise Scaling Diffusion Model for Spatial Time Series Imputation
A Graph-based Representation Framework for Trajectory Recovery via Spatiotemporal Interval-Informed Seq2Seq
Modeling Personalized Retweeting Behaviors for Multi-Stage Cascade Popularity Prediction
Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning
Game Theory and Economic Paradigms
Couples Can Be Tractable: New Algorithms and Hardness Results for the Hospitals/Residents Problem with Couples
Getting More by Knowing Less: Bayesian Incentive Compatible Mechanisms for Fair Division
Polynomial Time Presolve Algorithms for Rotation-Based Models Solving the Robust Stable Matching Problem
Vulnerabilities of Single-Round Incentive Compatibility in Auto-bidding: Theory and Evidence from ROI-Constrained Online Advertising Markets
Optimizing Prosumer Policies in Periodic Double Auctions Inspired by Equilibrium Analysis
Humans and AI
Multi-level Disentangling Network for Cross-Subject Emotion Recognition Based on Multimodal Physiological Signals
VSGT: Variational Spatial and Gaussian Temporal Graph Models for EEG-based Emotion Recognition
LitE-SNN: Designing Lightweight and Efficient Spiking Neural Network through Spatial-Temporal Compressive Network Search and Joint Optimization
Designing Behavior-Aware AI to Improve the Human-AI Team Performance in AI-Assisted Decision Making
DBPNet: Dual-Branch Parallel Network with Temporal-Frequency Fusion for Auditory Attention Detection
Apprenticeship-Inspired Elegance: Synergistic Knowledge Distillation Empowers Spiking Neural Networks for Efficient Single-Eye Emotion Recognition
Multi-scale Context-Aware Networks Based on Fragment Association for Human Activity Recognition
Dialogue Cross-Enhanced Central Engagement Attention Model for Real-Time Engagement Estimation
Knowledge Representation and Reasoning
Improved Encodings of Acyclicity for Translating Answer Set Programming into Integer Programming
Learning Conditional Preference Networks: An Approach Based on the Minimum Description Length Principle
Regression Residual Reasoning with Pseudo-labeled Contrastive Learning for Uncovering Multiple Complex Compositional Relations
Constructive Interpolation and Concept-Based Beth Definability for Description Logics via Sequents
CPa-WAC: Constellation Partitioning-based Scalable Weighted Aggregation Composition for Knowledge Graph Embedding
Towards a Principle-based Framework for Assessing the Contribution of Formulas on the Conflicts of Knowledge Bases
Optimisation and Approximation in Abstract Argumentation: The Case of Stable Semantics
NELLIE: A Neuro-Symbolic Inference Engine for Grounded, Compositional, and Explainable Reasoning
Machine Learning
Cutting the Black Box: Conceptual Interpretation of a Deep Neural Net with Multi-Modal Embeddings and Multi-Criteria Decision Aid
Deriving Provably Correct Explanations for Decision Trees: The Impact of Domain Theories
Ansatz-Agnostic Exponential Resource Saving in Variational Quantum Algorithms Using Shallow Shadows
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image Classification
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO
With a Little Help from Language: Semantic Enhanced Visual Prototype Framework for Few-Shot Learning
Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression
Breaking Barriers of System Heterogeneity: Straggler-Tolerant Multimodal Federated Learning via Knowledge Distillation
Global Optimality of Single-Timescale Actor-Critic under Continuous State-Action Space: A Study on Linear Quadratic Regulator
Structure-Preserving Physics-Informed Neural Networks with Energy or Lyapunov Structure
VCC-INFUSE: Towards Accurate and Efficient Selection of Unlabeled Examples in Semi-supervised Learning
Efficient Federated Multi-View Clustering with Integrated Matrix Factorization and K-Means
P2P: Transforming from Point Supervision to Explicit Visual Prompt for Object Detection and Segmentation
ParsNets: A Parsimonious Composition of Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning
Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection
SAEIR: Sequentially Accumulated Entropy Intrinsic Reward for Cooperative Multi-Agent Reinforcement Learning with Sparse Reward
Feature Norm Regularized Federated Learning: Utilizing Data Disparities for Model Performance Gains
Negative-Binomial Randomized Gamma Dynamical Systems for Heterogeneous Overdispersed Count Time Sequences
Unified View Imputation and Feature Selection Learning for Incomplete Multi-view Data
An Efficient Prototype-Based Clustering Approach for Edge Pruning in Graph Neural Networks to Battle Over-Smoothing
Offline Policy Learning via Skill-step Abstraction for Long-horizon Goal-Conditioned Tasks
HyQ: Hardware-Friendly Post-Training Quantization for CNN-Transformer Hybrid Networks
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms
Efficient and Stable Offline-to-online Reinforcement Learning via Continual Policy Revitalization
ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling
No Regularization Is Needed: Efficient and Effective Incomplete Label Distribution Learning
WPML3CP: Wasserstein Partial Multi-Label Learning with Dual Label Correlation Perspectives
Causality-enhanced Discreted Physics-informed Neural Networks for Predicting Evolutionary Equations
Efficiency Calibration of Implicit Regularization in Deep Networks via Self-paced Curriculum-Driven Singular Value Selection
Efficient Offline Meta-Reinforcement Learning via Robust Task Representations and Adaptive Policy Generation
Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy
MICRO: Model-Based Offline Reinforcement Learning with a Conservative Bellman Operator
Provable Acceleration of Nesterov’s Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks
A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points
LEAP: Optimization Hierarchical Federated Learning on Non-IID Data with Coalition Formation Game
Alleviating Imbalanced Pseudo-label Distribution: Self-Supervised Multi-Source Domain Adaptation with Label-specific Confidence
Machine Learning
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization
A Prior-information-guided Residual Diffusion Model for Multi-modal PET Synthesis from MRI
Let’s Start Over: Retraining with Selective Samples for Generalized Category Discovery
Partial Optimal Transport Based Out-of-Distribution Detection for Open-Set Semi-Supervised Learning
Hyperparameter Optimization Can Even Be Harmful in Off-Policy Learning and How to Deal with It
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning
Perturbation Guiding Contrastive Representation Learning for Time Series Anomaly Detection
A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods
MOSER: Learning Sensory Policy for Task-specific Viewpoint via View-conditional World Model
Finite-Time Convergence Rates of Decentralized Local Markovian Stochastic Approximation
Reconstruction Weighting Principal Component Analysis with Fusion Contrastive Learning
Nonconvex Multiview Subspace Clustering Framework with Efficient Method Designs and Theoretical Analysis
From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching
TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation
Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models
FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning
VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting
A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification
Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
Pointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes
BoostDream: Efficient Refining for High-Quality Text-to-3D Generation from Multi-View Diffusion
Efficient Multi-view Unsupervised Feature Selection with Adaptive Structure Learning and Inference
CONC: Complex-noise-resistant Open-set Node Classification with Adaptive Noise Detection
Skip-Timeformer: Skip-Time Interaction Transformer for Long Sequence Time-Series Forecasting
Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization
NanoAdapt: Mitigating Negative Transfer in Test Time Adaptation with Extremely Small Batch Sizes
Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning
SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting
AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers
FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning
vMFER: Von Mises-Fisher Experience Resampling Based on Uncertainty of Gradient Directions for Policy Improvement
PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds
Multidisciplinary Topics and Applications
Predictive Modeling with Temporal Graphical Representation on Electronic Health Records
Shadow-Free Membership Inference Attacks: Recommender Systems Are More Vulnerable Than You Thought
Geometry-Guided Conditional Adaptation for Surrogate Models of Large-Scale 3D PDEs on Arbitrary Geometries
Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks
MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction
VF-Detector: Making Multi-Granularity Code Changes on Vulnerability Fix Detector Robust to Mislabeled Changes
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces
Enhancing Length Generalization for Attention Based Knowledge Tracing Models with Linear Biases
OUCopula: Bi-Channel Multi-Label Copula-Enhanced Adapter-Based CNN for Myopia Screening Based on OU-UWF Images
A Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environments
SCTrans: Multi-scale scRNA-seq Sub-vector Completion Transformer for Gene-selective Cell Type Annotation
Enhancing Multimodal Knowledge Graph Representation Learning through Triple Contrastive Learning
Enhanced DouDiZhu Card Game Strategy Using Oracle Guiding and Adaptive Deep Monte Carlo Method
Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making
SACNN: Self Attention-based Convolutional Neural Network for Fraudulent Behaviour Detection in Sports
Dynamic Many-Objective Molecular Optimization: Unfolding Complexity with Objective Decomposition and Progressive Optimization
BeyondVision: An EMG-driven Micro Hand Gesture Recognition Based on Dynamic Segmentation
Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation
MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
ZeroDDI: A Zero-Shot Drug-Drug Interaction Event Prediction Method with Semantic Enhanced Learning and Dual-modal Uniform Alignment
Learning-Based Tracking-before-Detect for RF-Based Unconstrained Indoor Human Tracking
RSAP-DFM: Regime-Shifting Adaptive Posterior Dynamic Factor Model for Stock Returns Prediction
Domain Adaptive and Fine-grained Anomaly Detection for Single-cell Sequencing Data and Beyond
Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling
A Deep Reinforcement Learning Approach to Balance Viewport Prediction and Video Transmission in 360° Video Streaming
Heterogeneous Causal Metapath Graph Neural Network for Gene-Microbe-Disease Association Prediction
Natural Language Processing
MEDVOC: Vocabulary Adaptation for Fine-tuning Pre-trained Language Models on Medical Text Summarization
MMVQA: A Comprehensive Dataset for Investigating Multipage Multimodal Information Retrieval in PDF-based Visual Question Answering
Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognition
ECR-Chain: Advancing Generative Language Models to Better Emotion-Cause Reasoners through Reasoning Chains
GRASP: A Novel Benchmark for Evaluating Language GRounding and Situated Physics Understanding in Multimodal Language Models
Domain-Hierarchy Adaptation via Chain of Iterative Reasoning for Few-shot Hierarchical Text Classification
Bridge to Non-Barrier Communication: Gloss-Prompted Fine-Grained Cued Speech Gesture Generation with Diffusion Model
Reframing Spatial Reasoning Evaluation in Language Models: A Real-World Simulation Benchmark for Qualitative Reasoning
Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors
Separate in the Speech Chain: Cross-Modal Conditional Audio-Visual Target Speech Extraction
Innovative Directional Encoding in Speech Processing: Leveraging Spherical Harmonics Injection for Multi-Channel Speech Enhancement
Decoupling Breaks Data Barriers: A Decoupled Pre-training Framework for Multi-intent Spoken Language Understanding
Contextualized Speech Recognition: Rethinking Second-Pass Rescoring with Generative Large Language Models
NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli
Purpose Enhanced Reasoning through Iterative Prompting: Uncover Latent Robustness of ChatGPT on Code Comprehension
Beyond What If: Advancing Counterfactual Text Generation with Structural Causal Modeling
HyDiscGAN: A Hybrid Distributed cGAN for Audio-Visual Privacy Preservation in Multimodal Sentiment Analysis
It Ain’t That Bad: Understanding the Mysterious Performance Drop in OOD Generalization for Generative Transformer Models
TaD: A Plug-and-Play Task-Aware Decoding Method to Better Adapt LLMs on Downstream Tasks
Vision-fused Attack: Advancing Aggressive and Stealthy Adversarial Text against Neural Machine Translation
KG-CoT: Chain-of-Thought Prompting of Large Language Models over Knowledge Graphs for Knowledge-Aware Question Answering
Generate Synthetic Text Approximating the Private Distribution with Differential Privacy
Joint Multimodal Aspect Sentiment Analysis with Aspect Enhancement and Syntactic Adaptive Learning
Planning and Scheduling
Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains
ConstrainedZero: Chance-Constrained POMDP Planning Using Learned Probabilistic Failure Surrogates and Adaptive Safety Constraints
Laying the Foundations for Solving FOND HTN Problems: Grounding, Search, Heuristics (and Benchmark Problems)
A Better Approximation for Bipartite Traveling Tournament in Inter-League Sports Scheduling
Robotics
Integrating Intent Understanding and Optimal Behavior Planning for Behavior Tree Generation from Human Instructions
Physics-Informed Trajectory Prediction for Autonomous Driving under Missing Observation
A New Guaranteed Outlier Removal Method Based on Plane Constraints for Large-Scale LiDAR Point Cloud Registration
Search
Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy
ParaILP: A Parallel Local Search Framework for Integer Linear Programming with Cooperative Evolution Mechanism
ReinforceNS: Reinforcement Learning-based Multi-start Neighborhood Search for Solving the Traveling Thief Problem
Practical Anytime Algorithms for Judicious Partitioning of Active Directory Attack Graphs
Uncertainty in AI
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks
Proportion-based Sensitivity Analysis of Uncontrolled Confounding Bias in Causal Inference
AI for Good
Using Causal Inference to Investigate Contraceptive Discontinuation in Sub-Saharan Africa
Functional Graph Convolutional Networks: A Unified Multi-task and Multi-modal Learning Framework to Facilitate Health and Social-Care Insights
Fitness Activity Recognition Using a Novel Pressure Sensing Mat and Machine Learning for the Future of Accessible Training
VulnerabilityMap: An Open Framework for Mapping Vulnerability among Urban Disadvantaged Populations in the United States
An Embarrassingly Simple Approach to Enhance Transformer Performance in Genomic Selection for Crop Breeding
FairReFuse: Referee-Guided Fusion for Multi-Modal Causal Fairness in Depression Detection
For the Misgendered Chinese in Gender Bias Research: Multi-Task Learning with Knowledge Distillation for Pinyin Name Gender Prediction
Down the Toxicity Rabbit Hole: A Framework to Bias Audit Large Language Models with Key Emphasis on Racism, Antisemitism, and Misogyny
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach
Remote Sensing for Water Quality: A Multi-Task, Metadata-Driven Hypernetwork Approach
Energy-Efficient Missing Data Imputation in Wearable Health Applications: A Classifier-aware Statistical Approach
A Survival Guide for Iranian Women Prescribed by Iranian Women: Participatory AI to Investigate Intimate Partner Physical Violence in Iran
Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme
CDSTraj: Characterized Diffusion and Spatial-Temporal Interaction Network for Trajectory Prediction in Autonomous Driving
Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approach
Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method
Benchmarking Fish Dataset and Evaluation Metric in Keypoint Detection - Towards Precise Fish Morphological Assessment in Aquaculture Breeding
RisQNet: Rescuing SMEs from Financial Shocks with a Novel Networked-Loan Risk Assessment
Understanding Public Perception Towards Weather Disasters Through the Lens of Metaphor
Domain Adaptation with Joint Loss for Consistent Regression and Ordinal Classification in the Proxy Means Test for Poverty Targeting
Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Method
Unmasking Societal Biases in Respiratory Support for ICU Patients through Social Determinants of Health
Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation
From Pink and Blue to a Rainbow Hue! Defying Gender Bias through Gender Neutralizing Text Transformations
SUKHSANDESH: An Avatar Therapeutic Question Answering Platform for Sexual Education in Rural India
A Novel GAN Approach to Augment Limited Tabular Data for Short-Term Substance Use Prediction
Fuel-Saving Route Planning with Data-Driven and Learning-Based Approaches – A Systematic Solution for Harbor Tugs
From Pixels to Progress: Generating Road Network from Satellite Imagery for Socioeconomic Insights in Impoverished Areas
LEEC for Judicial Fairness: A Legal Element Extraction Dataset with Extensive Extra-Legal Labels
MuseCL: Predicting Urban Socioeconomic Indicators via Multi-Semantic Contrastive Learning
Detecting AI-Generated Sentences in Human-AI Collaborative Hybrid Texts: Challenges, Strategies, and Insights
Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach
DeepLight: Reconstructing High-Resolution Observations of Nighttime Light With Multi-Modal Remote Sensing Data
Safeguarding Sustainable Cities: Unsupervised Video Anomaly Detection through Diffusion-based Latent Pattern Learning
AI, Arts & Creativity
Paintings and Drawings Aesthetics Assessment with Rich Attributes for Various Artistic Categories
Arrange, Inpaint, and Refine: Steerable Long-term Music Audio Generation and Editing via Content-based Controls
MuChin: A Chinese Colloquial Description Benchmark for Evaluating Language Models in the Field of Music
End-to-End Real-World Polyphonic Piano Audio-to-Score Transcription with Hierarchical Decoding
DP-Font: Chinese Calligraphy Font Generation Using Diffusion Model and Physical Information Neural Network
Human-Centred AI
Are They the Same Picture? Adapting Concept Bottleneck Models for Human-AI Collaboration in Image Retrieval
Human-Agent Cooperation in Games under Incomplete Information through Natural Language Communication
Towards Proactive Interactions for In-Vehicle Conversational Assistants Utilizing Large Language Models
The Role of Perception, Acceptance, and Cognition in the Usefulness of Robot Explanations
XAI-Lyricist: Improving the Singability of AI-Generated Lyrics with Prosody Explanations
Survey Track
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges
A Survey on Extractive Knowledge Graph Summarization: Applications, Approaches, Evaluation, and Future Directions
Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models
A Comprehensive Survey and Taxonomy on Point Cloud Registration Based on Deep Learning
Sister Conferences Best Papers
Inferring Ontological Categories of OWL Classes Using Foundational Rules (Extended Abstract)
Planning for Temporally Extended Goals in Pure-Past Linear Temporal Logic (Extended Abstract)
Selective Learning for Sample-Efficient Training in Multi-Agent Sparse Reward Tasks (Extended Abstract)
Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains (Extended Abstract)
Capturing (Optimal) Relaxed Plans with Stable and Supported Models of Logic Programs (Extended Abstract)
Defending Against Backdoor Attacks by Layer-wise Feature Analysis (Extended Abstract)
A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings (Extended Abstract)
GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search (Extended Abstract)
MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale (Extended Abstract)
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling (Extended Abstract)
Content Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples (Extended Abstract)
Journal Track
Hybrid planning for challenging construction problems: An Answer Set Programming approach (Abstract Reprint)
Negative Human Rights as a Basis for Long-term AI Safety and Regulation (Abstract Reprint)
A differentiable first-order rule learner for inductive logic programming (Abstract Reprint)
SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes (Abstract Reprint)
On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint)
Mitigating robust overfitting via self-residual-calibration regularization (Abstract Reprint)
Performative Ethics From Within the Ivory Tower: How CSPractitioners Uphold Systems of Oppression (Abstract Reprint)
Hierarchical Decompositions and Termination Analysis for Generalized Planning (Abstract Reprint)
Doctoral Consortium
Towards Revolutionized Smart Grids: An AI-Driven Broker for Improved Operational Efficiency
Causal Graph Modeling with Deep Neural Engines for Strong Abstract Reasoning in Language and Vision
Bio-inspired Dynamic and Decentralized Online Learning in Uninformed Heterogeneous Multi-Agent Environments
Early Career
Human-Robot Alignment through Interactivity and Interpretability: Don't Assume a ``Spherical Human''
Human-AI Interaction Generation: A Connective Lens for Generative AI and Procedural Content Generation
The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence
Towards a Theory of Machine Learning on Graphs and its Applications in Combinatorial Optimization
Transforming Recommender Systems: Balancing Personalization, Fairness, and Human Values
A Little of That Human Touch: Achieving Human-Centric Explainable AI via Argumentation
Demo Track
REAVER: Real-time Earthquake Prediction with Attention-based Sliding-Window Spectrograms
FD-UAD: Unsupervised Anomaly Detection Platform Based on Defect Autonomous Imaging and Enhancement
Integrating LLM, VLM, and Text-to-Image Models for Enhanced Information Graphics: A Methodology for Accurate and Visually Engaging Visualizations
NegoLog: An Integrated Python-based Automated Negotiation Framework with Enhanced Assessment Components
An Interactive Human-Machine Learning Interface for Collecting and Learning from Complex Annotations
Plug-and-Play Unsupervised Fault Detection and Diagnosis for Complex Industrial Monitoring
Artificial Intelligence-Driven Video Indexing for Rapid Surveillance Footage Summarization and Review
Demo: Enhancing Wildlife Acoustic Data Annotation Efficiency through Transfer and Active Learning
Using Large Language Models and Recruiter Expertise for Optimized Multilingual Job Offer – Applicant CV Matching
NEGOTIATOR: A Comprehensive Framework for Human-Agent Negotiation Integrating Preferences, Interaction, and Emotion
AUTODRAITEC: An Infrastructure-Based AUTOnomous DRiving System Using Artificial Intelligence and TEleCommunication Technologies
SPARK: Harnessing Human-Centered Workflows with Biomedical Foundation Models for Drug Discovery
Real-time Multi-modal Object Detection and Tracking on Edge for Regulatory Compliance Monitoring
ReportParse: A Unified NLP Tool for Extracting Document Structure and Semantics of Corporate Sustainability Reporting
LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks
XGA-Osteo: Towards XAI-Enabled Knee Osteoarthritis Diagnosis with Adversarial Learning
Reinforcement Learning for Athletic Intelligence: Lessons from the 1st “AI Olympics with RealAIGym” Competition
Upgrading Search Applications in the Era of LLMs: A Demonstration with Practical Lessons