ECAI 2023

Name: ECAI 2023 | 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Krakow, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023)
Brand: IOS Press,US
Price: 883.99 EUR
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26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Krakow, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023)

Kobi Gal Ann Nowe Grzegorz J. Nalepa Roy Fairstein Roxana Radulescu(Editor)

IOS Press,US

1st Edition

Published on 15. October 2023

3326 pages

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978-1-64368-437-6 (ISBN)

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Content

Intro
Title Page
Preface
Message from the Conference Organizers
Conference Organization
Sponsorship and Support
Reviewers
PAIS 2023 Foreword
PAIS 2023 Programme Committee
Contents
ECAI Papers
Learning Task Automata for Reinforcement Learning Using Hidden Markov Models
On the Effectiveness of Compact Strategies for Opinion Diffusion in Social Environments
Hierarchical Text Classification Using Contrastive Learning Informed Path Guided Hierarchy
Reconciling SHACL and Ontologies: Semantics and Validation via Rewriting
Towards a Neuronally Consistent Ontology for Robotic Agents
Action-Failure Resilient Planning
Fair Rent Division on a Budget Revisited
TrojBits: A Hardware Aware Inference-Time Attack on Transformer-Based Language Models
A Siamese Based System for City Verification
Complexity of Verification and Existence Problems in Epistemic Argumentation Framework
Robust Federated Learning Method Against Data and Model Poisoning Attacks with Heterogeneous Data Distribution
Causally Disentangled Generative Variational AutoEncoder
CAFIN: Centrality Aware Fairness Inducing IN-Processing for Unsupervised Representation Learning on Graphs
Long-Tail Theory Under Gaussian Mixtures
On Contrastive Explanations for Tree-Based Classifiers
On the Manipulability of Maximum Vertex-Weighted Bipartite b-Matching Mechanisms
A Bilevel Formalism for the Peer-Reviewing Problem
Reachability Poorman Discrete-Bidding Games
SpArX: Sparse Argumentative Explanations for Neural Networks
From Intermediate Representations to Explanations: Exploring Hierarchical Structures in NLP
Investigating Neural Fit Approaches for Sentence Embedding Model Paradigms
Partial Compilation of SAT Using Selective Backbones
Cost-Awareness in Multi-Agent Active Search
No Agreement Without Loss: Learning and Social Choice in Peer Review
Cooperative Thresholded Lasso for Sparse Linear Bandit
Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries
Resource-constrained knowledge diffusion processes inspired by human peer learning
Neural Network-Based Rule Models with Truth Tables
Diverse, Top-k, and Top-Quality Planning Over Simulators
Pareto Rank-Preserving Supernetwork for Hardware-Aware Neural Architecture Search
On the Structural Complexity of Grounding - Tackling the ASP Grounding Bottleneck via Epistemic Programs and Treewidth
Enhancing Hybrid CP-SAT Search for Disjunctive Scheduling
Expediting Self-Play Learning in AlphaZero-Style Game-Playing Agents
Representative Answer Sets: Collecting Something of Everything
FOND Planning for Pure-Past Linear Temporal Logic Goals
Leveraging Error Patterns to Correct Prediction Intervals
On Sustainable Ride Pooling Through Conditional Expected Value Decomposition
High-Multiplicity Fair Allocation Using Parametric Integer Linear Programming
Efficiently Computing Smallest Agreeable Sets
A Semantic Approach to Decidability in Epistemic Planning
Credal Learning: Weakly Supervised Learning from Credal Sets
Enhancing OOD Generalization in Offline Reinforcement Learning with Energy-Based Policy Optimization
A Flexible Debiasing Framework for Fair Heterogeneous Information Network Embedding
Theoretical Remarks on Feudal Hierarchies and Reinforcement Learning
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning
Obstruction Logic: A Strategic Temporal Logic to Reason About Dynamic Game Models
Cache-Efficient Dynamic Programming MDP Solver
Shrink-Perturb Improves Architecture Mixing During Population Based Training for Neural Architecture Search
Evaluating Explanation Methods for Vision-and-Language Navigation
Efficient Algorithms for Monroe and CC Rules in Multi-Winner Elections with (Nearly) Structured Preferences
Dual-Scale Interest Extraction Framework with Self-Supervision for Sequential Recommendation
Selective Learning for Sample-Efficient Training in Multi-Agent Sparse Reward Tasks
Learning Dual Mean Field Games on Graphs
FASTC: A Fast Attentional Framework for Semantic Traversability Classification Using Point Cloud
Region-Aware Dynamic Filtering Network for 3D Hand Reconstruction
Diffusion Model for Camouflaged Object Detection
PARIS: Planning Algorithms for Reconfiguring Independent Sets
Deep Reinforcement Learning with Implicit Imitation for Lane-Free Autonomous Driving
Abductive Explanations of Classifiers Under Constraints: Complexity and Properties
Counterfactual Reasoning for Bias Evaluation and Detection in a Fairness Under Unawareness Setting
Rectifying Binary Classifiers
Rank-Envy-Freeness in Roommate Matchings
Learning Logic Programs by Combining Programs
TAOTF: A Two-Stage Approximately Orthogonal Training Framework in Deep Neural Networks
Worrisome Properties of Neural Network Controllers and Their Symbolic Representations
Enhancing Document-Level Relation Extraction with Relation-Specific Entity Representation and Evidence Sentence Augmentation
LTLf Best-Effort Synthesis in Nondeterministic Planning Domains
Aggregating Correlated Estimations with (Almost) no Training
PiercingEye: Identifying Both Faint and Distinct Clues for Explainable Fake News Detection with Progressive Dynamic Graph Mining
Compilation of Tight ASP Programs
Antecedent Predictions Are More Important Than You Think: An Effective Method for Tree-Based Code Generation
Distributionally Robust Cross Subject EEG Decoding
What Wikipedia Misses About Yuriko Nakamura? Predicting Missing Biography Content by Learning Latent Life Patterns
Reinforcement Learning for Bandits with Continuous Actions and Large Context Spaces
Heteroscedastic Causal Structure Learning
Learning in Teams: Peer Evaluation for Fair Assessment of Individual Contributions
Exploiting Epistemic Uncertainty at Inference Time for Early-Exit Power Saving
Settling the Score: Portioning with Cardinal Preferences
Data-Driven Self-Supervised Graph Representation Learning
Algorithmic Recognition of 2-Euclidean Preferences
Towards a Rigorous Calibration Assessment Framework: Advancements in Metrics, Methods, and Use
A Novel Differentiable Rank Learning Method Towards Stock Movement Quantile Forecasting
Identifying the Defective: Detecting Damaged Grains for Cereal Appearance Inspection
On the Robustness of Split Learning Against Adversarial Attacks
Multi-Unit Auction over a Social Network
Incomplete Bipolar Argumentation Frameworks
Structured Sparse Multi-Task Learning with Generalized Group Lasso
On Solution Discovery via Reconfiguration
Optimal Alignment of Temporal Knowledge Bases
Failure Handling in BDI Plans via Runtime Enforcement
SENA: Similarity-Based Error-Checking of Neural Activations
Using Weighted Matching to Solve 2-Approval/Veto Control and Bribery
Generalizing Similarity in Noisy Setups: The DIBS Phenomenon
Scaling-Up LAO* in FOND Planning: An Ablation Study
Revision Transformers: Instructing Language Models to Change Their Values
Double Logistic Regression Approach to Biased Positive-Unlabeled Data
OER: Offline Experience Replay for Continual Offline Reinforcement Learning
Strategy Repair in Reachability Games
Iterative Reward Shaping Using Human Feedback for Correcting Reward Misspecification
EFx Budget-Feasible Allocations with High Nash Welfare
Towards Trustworthy NLP: An Adversarial Robustness Enhancement Based on Perplexity Difference
Decidable Fragments of LTLf Modulo Theories
Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions
Evolutionary Explainable Rule Extraction from (Modal) Random Forests
A Hybrid Approach to Preference Learning with Interaction Terms
Conditionally Acyclic CO-Networks for Efficient Preferential Optimization
A Semantics-Driven Methodology for High-Quality Image Annotation
RHALE: Robust and Heterogeneity-Aware Accumulated Local Effects
Dynamic Causality
Do Not Trust Me: Explainability Against Text Classification
Approximate Model-Based Shielding for Safe Reinforcement Learning
Effective and Efficient Community Search with Graph Embeddings
Pretraining the Vision Transformer Using Self-Supervised Methods for Vision Based Deep Reinforcement Learning
Declarative Encoding of Fairness in Logic Tensor Networks
Generosity and the Emergence of Forgiveness in the Donation Game
On the Notion of Envy Among Groups of Agents in House Allocation Problems
XGBD: Explanation-Guided Graph Backdoor Detection
Mitigating Long-Tail Language Representation Collapsing via Cross-Lingual Bootstrapped Unsupervised Fine-Tuning
Is Performance Fairness Achievable in Presence of Attackers Under Federated Learning?
Take Expert Advice Judiciously: Combining Groupwise Calibrated Model Probabilities with Expert Predictions
Bridging the Transparency Gap: What Can Explainable AI Learn from the AI Act?
Omega-Regular Reward Machines
Exploring the Feasibility of Physical Adversarial Attacks: A Cybersecurity Study
Evolving Dictionary Representation for Few-Shot Class-Incremental Learning
Leximin Approximation: From Single-Objective to Multi-Objective
Dimensions of Similarity: Towards Interpretable Dimension-Based Text Similarity
Group Activity Recognition in Basketball Tracking Data - Neural Embeddings in Team Sports (NETS)
GraphSA: Smart Contract Vulnerability Detection Combining Graph Neural Networks and Static Analysis
Multi-Domain Learning from Insufficient Annotations
Preserving Semantics in Textual Adversarial Attacks
Sensitivity Analysis for Saturated Post-Hoc Optimization in Classical Planning
Gaifman Graphs in Lifted Planning
LoSS: Local Structural Separation Hypergraph Convolutional Neural Network
Reinforcement Learning with Reward Machines in Stochastic Games
Reasoning Guided by a Manual: Context-Aware Image Captioning with Novel Objects
DTBS: Dual-Teacher Bi-Directional Self-Training for Domain Adaptation in Nighttime Semantic Segmentation
Combating Short Circuit Behavior in Natural Language Reasoning: Crossover and Mutation Operations for Enhanced Robustness
From Decision Trees to Explained Decision Sets
Diversified Prior Knowledge Enhanced General Language Model for Biomedical Information Retrieval
Exploration and Exploitation in Hierarchical Reinforcement Learning with Adaptive Scheduling
Oracle-Based Local Search for Pseudo-Boolean Optimization
T-VAKS: A Tutoring-Based Multimodal Dialog System via Knowledge Selection
Multi-Modal Fusion with Semantic Supervision for Radiology Report Generation
Offline Decentralized Multi-Agent Reinforcement Learning
Transferring Procedural Knowledge Across Commonsense Tasks
Grouped Multi-Task Learning with Hidden Tasks Enhancement
FedPerturb: Covert Poisoning Attack on Federated Learning via Partial Perturbation
SMT-Based Satisfiability Checking of Strategic Metric Temporal Logic
Complexity of Control by Adding or Deleting Edges in Graph-Restricted Weighted Voting Games
The Leximin Approach for a Sequence of Collective Decisions
Robust Assignment of Labels for Active Learning with Sparse and Noisy Annotations
Automatic Parallel Portfolio Selection
Answer Set Automata: A Learnable Pattern Specification Framework for Complex Event Recognition
Reducing Oversmoothing in Graph Neural Networks by Changing the Activation Function
On Explaining Agent Behaviour via Root Cause Analysis: A Formal Account Grounded in Theory of Mind
Understanding and Improving Neural Active Learning on Heteroskedastic Distributions
Counterfactual Prediction Under Selective Confounding
Gated Adapters for Multi-Domain Neural Machine Translation
Cartesian Abstractions and Saturated Cost Partitioning in Probabilistic Planning
ALFR++: A Novel Algorithm for Learning Adversarial Fair Representations
Approximate Data Deletion in Generative Models
Satisfaction-Maximizing Optimal Stopping
Extracting and Exploiting Bounds of Numeric Variables for Optimal Linear Numeric Planning
Towards Flexible Time-to-Event Modeling: Optimizing Neural Networks via Rank Regression
Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering
Self-Expressive Network-Based Subspace Clustering for Deep Embedding
S2M: Converting Single-Turn to Multi-Turn Datasets for Conversational Question Answering
Mechanism Design for Ad Auctions with Display Prices
Theoretically Guaranteed Policy Improvement Distilled from Model-Based Planning
Spectral Normalized-Cut Graph Partitioning with Fairness Constraints
ESSL: Enhanced Spatio-Temporal Self-Selective Learning Framework for Unsupervised Video Anomaly Detection
High Probability Analysis for Non-Convex Stochastic Optimization with Clipping
BEDCOE: Borderline Enhanced Disjunct Cluster Based Oversampling Ensemble for Online Multi-Class Imbalance Learning
Integrated Private Data Trading Systems for Data Marketplaces
Unsupervised Graph Structure-Assisted Personalized Federated Learning
DeepDiscord: Dual Contrastive Coding for Transferable Time Series Anomaly Detection
Neural Architecture Search for Explainable Networks
BMIPN: A Biased Multi-Granularity Interaction Prototype Network for Few-Shot Relation Extraction
A Model-Theoretic Approach to Belief Revision in Multi-Agent Belief Logic and Its Syntactic Characterizations
FBC: Fusing Bi-Encoder and Cross-Encoder for Long-Form Text Matching
Model-Based Reinforcement Learning with Multi-Step Plan Value Estimation
Accelerating SAT-Based HTN Plan Verification by Exploiting Data Structures from HTN Planning
Verifying Belief-Based Programs via Symbolic Dynamic Programming
Diffusion Multi-Unit Auctions with Diminishing Marginal Utility Buyers
Label Aggregation with Self-Supervision Enhanced Graph Transformer
POINE2: Improving Poincare Embeddings for Hierarchy-Aware Complex Query Reasoning over Knowledge Graphs
Multilingual Lexical Simplification via Paraphrase Generation
QCCDM: A Q-Augmented Causal Cognitive Diagnosis Model for Student Learning
Efficient Information Modulation Network for Image Super-Resolution
Aspect-Oriented Opinion Alignment Network for Aspect-Based Sentiment Classification
A Dynamic Selective Parameter Sharing Mechanism Embedded with Multi-Level Reasoning Abstractions
Comment-Aware Multi-Modal Heterogeneous Pre-Training for Humor Detection in Short-Form Videos
Epistemic JAADL: A Modal Logic for Joint Abilities with Imperfect Information
Revisiting Graph Contrastive Learning for Anomaly Detection
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving
Online Algorithms for Matchings with Proportional Fairness Constraints and Diversity Constraints
Degradation-Resistant Offline Optimization via Accumulative Risk Control
Multi-Agent Cooperative Games Using Belief Map Assisted Training
Decentralized Local Updates with Dual-Slow Estimation and Momentum-Based Variance-Reduction for Non-Convex Optimization
Dynamic Graph Convolutional Network with Attention Fusion for Traffic Flow Prediction
Dynamic Workload-Aware Bike Rebalancing for Bike-Sharing Systems
R-STAR: Robust Self-Taught Task-Wise Reweighting for Rehearsal-Based Class Incremental Learning
Semantic-Aware Dual Contrastive Learning for Multi-Label Image Classification
Letting Go of Self-Domain Awareness: Multi-Source Domain-Adversarial Generalization via Dynamic Domain-Weighted Contrastive Transfer Learning
MFC: A Multishot Approach to Federated Data Clustering
Improving Bi-Objective Shortest Path Search with Early Pruning
FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion Recognition
Adversarial Benchmark Evaluation Rectified by Controlling for Difficulty
A Bayesian Optimization Framework for Finding Local Optima in Expensive Multimodal Functions
H2T-FAST: Head-to-Tail Feature Augmentation by Style Transfer for Long-Tailed Recognition
One-Class Classification Approach to Variational Learning from Biased Positive Unlabeled Data
A Local Non-Additive Framework for Explaining Black-Box Predictive Models
Multi-Source Domain Adaptation Through Dataset Dictionary Learning in Wasserstein Space
Graph-Based Abstractive Summarization of Extracted Essential Knowledge for Low-Resource Scenarios
On Observability Analysis in Multiagent Systems
Blame Attribution for Multi-Agent Path Finding Execution Failures
Fast Pareto Optimization Using Sliding Window Selection
MaxSAT-Based Inconsistency Measurement
Piecewise-Stationary Combinatorial Semi-Bandit with Causally Related Rewards
THUNDER: Named Entity Recognition Using a Teacher-Student Model with Dual Classifiers for Strong and Weak Supervisions
Detecting Out-of-Distribution Objects Using Neuron Activation Patterns
Graph Neural Networks for Mapping Variables Between Programs
Using Earley Parser for Recognizing Totally Ordered Hierarchical Plans
Transparency in Sum-Product Network Decompilation
CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer
Story Ending Generation Using Commonsense Casual Reasoning and Graph Convolutional Networks
Adversarial Discriminator to Mitigate Gender Bias in Abusive Language Detection
Anticipating Responsibility in Multiagent Planning
AlegAATr the Bandit
Stock Movement Prediction via Attention-Aware Multi-Order Relation Graph Neural Network
Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning
Overlay Neural Networks for Heterophilous Graphs
Generating Replanning Goals Through Multi-Objective Optimization in Response to Execution Observation
Exploring Information Bottleneck for Weakly Supervised Semantic Segmentation
Active Finetuning Protein Language Model: A Budget-Friendly Method for Directed Evolution
The Problem of Coherence in Natural Language Explanations of Recommendations
An Easy Rejection Sampling Baseline via Gradient Refined Proposals
Fair Latent Deep Generative Models (FLDGMs) for Syntax-Agnostic and Fair Synthetic Data Generation
Instance-Aware Diffusion Implicit Process for Box-Based Instance Segmentation
Making Friends in the Dark: Ad Hoc Teamwork Under Partial Observability
Specifying Prior Beliefs over DAGs in Deep Bayesian Causal Structure Learning
Seq2Space: A Lightweight Solution for Sequence Modelling
SUDS: Sanitizing Universal and Dependent Steganography
How Should I Compute My Candidates? A Taxonomy and Classification of Diagnosis Computation Algorithms
Disentangling Interaction Using Maximum Entropy Reinforcement Learning in Multi-Agent Systems
GENEMASK: Fast Pretraining of Gene Sequences to Enable Few-Shot Learning
Learning to Collaborate by Grouping: A Consensus-Oriented Strategy for Multi-Agent Reinforcement Learning
Capsule Network with Label Dependency Modeling for Multi-Label Emotion Classification
Causal Discovery and Knowledge Injection for Contestable Neural Networks
Symbolic Knowledge-Extraction Evaluation Metrics: The FiRe Score
Rationale-Guided Few-Shot Classification to Detect Abusive Language
A Paraconsistency Framework for Inconsistency Handling in Qualitative Spatial and Temporal Reasoning
Towards Feasible Counterfactual Explanations: A Taxonomy Guided Template-Based NLG Method
Associative Memories in the Feature Space
Stackelberg Attacks on Auctions and Blockchain Transaction Fee Mechanisms
Synthesis of Procedural Models for Deterministic Transition Systems
The Emotions of the Crowd: Learning Image Sentiment from Tweets via Cross-Modal Distillation
Reinforcement Learning in RDPs by Combining Deep RL with Automata Learning
Cognitive Effects in Large Language Models
Truthful and Equitable Lateral Transshipment in Multi-Retailer Systems
Balancing Fairness and Efficiency in 3D Repeated Matching in Ridesharing
Uncertain Relational Hypergraph Attention Networks for Document-Level Event Factuality Identification
Create and Find Flatness: Building Flat Training Spaces in Advance for Continual Learning
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study
A Simple Debiasing Framework for Out-of-Distribution Detection in Human Action Recognition
XFLT: Exploring Techniques for Generating Cross Lingual Factually Grounded Long Text
Progression for Monitoring in Temporal ASP
Minimum Target Sets in Non-Progressive Threshold Models: When Timing Matters
Graduality in Probabilistic Argumentation Frameworks
Lifted Successor Generation by Maximum Clique Enumeration
Motivated Agent with Semantic Memory
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging
GridFormer: Spatial-Temporal Transformer Network for Citywide Crowd Flow Prediction
Unit Refutations of Difference Constraint Systems
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks
On the Price of Fairness in the Connected Discrete Cake Cutting Problem
Decoding Realistic Images from Brain Activity with Contrastive Self-Supervision and Latent Diffusion
Tuning in to Neural Encoding: Linking Human Brain and Artificial Supervised Representations of Language
SPAT: Semantic-Preserving Adversarial Transformation for Perceptually Similar Adversarial Examples
BridgeHand2Vec Bridge Hand Representation
Anytime Index-Based Search Method for Large-Scale Simultaneous Coalition Structure Generation and Assignment
Unsupervised Zero-Shot Learning for Achieve Cross-Modal Alignment with Counterfactuals
FedCoop: Cooperative Federated Learning for Noisy Labels
User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations
Intractability of Optimal Multi-Agent Pathfinding on Directed Graphs
Tab-Attention: Self-Attention-Based Stacked Generalization for Imbalanced Credit Default Prediction
High Dynamic Range Image Reconstruction via Deep Explicit Polynomial Curve Estimation
Improved Analysis of Greedy Algorithm on k-Submodular Knapsack
NEHATE: Large-Scale Annotated Data Shedding Light on Hate Speech in Nepali Local Election Discourse
Local context is not enough! Towards Query Semantic and Knowledge Guided Multi-Span Medical Question Answering
Do Topic and Causal Consistency Affect Emotion Cognition? A Graph Interactive Network for Conversational Emotion Detection
Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation
Uniform Training and Marginal Decoding for Multi-Reference Question-Answer Generation
SCRAPS: Speech Contrastive Representations of Acoustic and Phonetic Spaces
On the Learning Dynamics of Attention Networks
A Logic-Based Framework for Explainable Agent Scheduling Problems
PLEASE: Generating Personalized Explanations in Human-Aware Planning
Neuro-Symbolic Procedural Semantics for Reasoning-Intensive Visual Dialogue Tasks
Automatic Radiology Report Generation by Learning with Increasingly Hard Negatives
Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm
An Empirical Study of Retrieval-Enhanced Graph Neural Networks
Improving Visual Reinforcement Learning with Discrete Information Bottleneck Approach
How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?
VMBRL3: A Simple Visual Model-Based Reinforcement Learning Framework for Continuous Control
BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization
LFAA: Crafting Transferable Targeted Adversarial Examples with Low-Frequency Perturbations
Towards Legal Judgment Summarization: A Structure-Enhanced Approach
A Conditional Denoising Diffusion Probabilistic Model for Radio Interferometric Image Reconstruction
MonoSKD: General Distillation Framework for Monocular 3D Object Detection via Spearman Correlation Coefficient
Fair Few-Shot Learning with Auxiliary Sets
Attention Based Models for Cell Type Classification on Single-Cell RNA-Seq Data
GAN-Generated Faces Detection: A Survey and New Perspectives
Investigating the Learning Behaviour of In-Context Learning: A Comparison with Supervised Learning
Using Self-Supervised Dual Constraint Contrastive Learning for Cross-Modal Retrieval
Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning
SDV: Simple Double Validation Model-Based Offline Reinforcement Learning
A Convolutional Neural Network Approach to General Game Playing
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Tickets
WeaGAN: Weather-Aware Graph Attention Network for Traffic Prediction
CCPO: Conservatively Constrained Policy Optimization Using State Augmentation
A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates
Normalized Stochastic Heavy Ball with Adaptive Momentum
A Landmark-Cut Heuristic for Lifted Optimal Planning
TreeFlow: Going Beyond Tree-Based Parametric Probabilistic Regression
On the Variation of Max Regret with Respect to the Scaling of the Objectives
Enforcing Natural Properties of Choice Functions, with Application for Combination
Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning
GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing
Contrastive Learning with Diverse Samples
Adaptive Self-Supervised Continual Learning
Deep Ensemble Robustness by Adaptive Sampling in Dropout-Based Simultaneous Training
Online Privacy Preservation for Camera-Incremental Person Re-Identification
Enhancing Text Generation with Cooperative Training
DPBERT: Efficient Inference for BERT Based on Dynamic Planning
Cardsformer: Grounding Language to Learn a Generalizable Policy in Hearthstone
Visualization Enhancement of Saliency Methods Based on the Sliding Window Mechanism
Characterizations of Network Auctions and Generalizations of VCG
Identical and Fraternal Twins: Fine-Grained Semantic Contrastive Learning of Sentence Representations
Identifying Helpful Learnwares Without Examining the Whole Market
IPERS: Individual Prioritized Experience Replay with Subgoals for Sparse Reward Multi-Agent Reinforcement Learning
Domain Knowledge Injection in Bayesian Search for New Materials
Task-Prompt Generalised World Model in Multi-Environment Offline Reinforcement Learning
Task-Sensitive Discriminative Mutual Attention Network for Few-Shot Learning
Fingerprint Attack: Client De-Anonymization in Federated Learning
Specializing Small Language Models Towards Complex Style Transfer via Latent Attribute Pre-Training
Rethinking Temporal Information in Session-Based Recommendation: A Position-Agnostic Approach
A Declarative Approach to Compact Controllers for FOND Planning via Answer Set Programming
Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties
Instance-Wise Adaptive Tuning and Caching for Vision-Language Models
Enhancing Link Prediction with Self-Discriminating Augmentation for Structure-Aware Contrastive Learning
Model-Based Offline Policy Optimization with Adversarial Network
Reinforcement Learning by Guided Safe Exploration
Data-Free Class-Incremental Learning with Implicit Representation of Prototypes
Enhanced Machine Reading Comprehension Method for Aspect Sentiment Quadruplet Extraction
Towards Abstractive Timeline Summarisation Using Preference-Based Reinforcement Learning
Deep Interactions-Boosted Embeddings for Link Prediction on Knowledge Graph
Argument Attribution Explanations in Quantitative Bipolar Argumentation Frameworks
CERM: Context-Aware Literature-Based Discovery via Sentiment Analysis
Highly-Efficient Robinson-Foulds Distance Estimation with Matrix Correction
Fair Deep Reinforcement Learning with Preferential Treatment
Boosting Visual Question Answering Through Geometric Perception and Region Features
Region-Specific Prototype Customization for Weakly Supervised Semantic Segmentation
ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning
Invisible Backdoor Attacks Using Data Poisoning in Frequency Domain
Micro-Expression Spotting Method Based on AU Prototype
Improving Text Semantic Similarity Modeling Through a 3D Siamese Network
Knowledge Injection for Multiagent Systems via Counterfactual Perception Shaping
Privacy-Enhanced AI Assistants Based on Dialogues and Case Similarity
Multi-Aspect Enhanced Convolutional Neural Networks for Knowledge Graph Completion
Siamese Representation Learning for Unsupervised Relation Extraction
Information Bound and Its Applications in Bayesian Neural Networks
Uncertainty-Driven Trajectory Truncation for Data Augmentation in Offline Reinforcement Learning
Revisiting the Efficiency-Accuracy Tradeoff in Adapting Transformer Models via Adversarial Fine-Tuning
Read Key Points: Dialogue-Grounded Knowledge Points Generation with Multi-Level Salience-Aware Mixture
Individual Fairness Under Uncertainty
DCNet: Weakly Supervised Saliency Guided Dual Coding Network for Visual Sentiment Recognition
Adam Accumulation to Reduce Memory Footprints of Both Activations and Gradients for Large-Scale DNN Training
Structure-Aware Group Discrimination with Adaptive-View Graph Encoder: A Fast Graph Contrastive Learning Framework
Time-Series Data Imputation via Realistic Masking-Guided Tri-Attention Bi-GRU
Deep Unsupervised Hashing with Hyperbolic Multi-Structure Learning
MIATS:A Chinese Spelling Error Correction Algorithm Based on Multimodal Information Alignment of Three-Towers Structure
XFed: Improving Explainability in Federated Learning by Intersection Over Union Ratio Extended Client Selection
Improving Adversarial Transferability with Ghost Samples
Turn on the Right Track: Weakly Supervised Video Moment Retrieval with Self-Improving Query Reconstruction
Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation
Robustness Testing for Multi-Agent Reinforcement Learning: State Perturbations on Critical Agents
Deep Co-Training for Cross-Modality Medical Image Segmentation
Grafting Fine-Tuning and Reinforcement Learning for Empathetic Emotion Elicitation in Dialog Generation
Ensembling Uncertainty Measures to Improve Safety of Black-Box Classifiers
PMAA: A Progressive Multi-Scale Attention Autoencoder Model for High-Performance Cloud Removal from Multi-Temporal Satellite Imagery
PAIS Papers
A Neuro-Symbolic Approach for Non-Intrusive Load Monitoring
Environmentally-Aware Bundle Recommendation Using the Choquet Integral
FMTESTING: A FEATUREIDE Plug-in for Automated Feature Model Analysis and Diagnosis
CICERO: A GPT2-Based Writing Assistant to Investigate the Effectiveness of Specialized LLMs' Applications in e-Justice
Acquisition and Formalization of Tacit Knowledge for Value Chain Generation in Local Production Networks
Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care
Creating Explainable Dynamic Checklists via Machine Learning to Ensure Decent Working Environment for All: A Field Study with Labour Inspections
The Monad Platform - Temporal Aspects in Behavioral Modeling
Online Evaluation of Tail Project Boosting in Citizen Science
Classifying Aircraft Categories from Magnetometry Data Using a Hypotheses-Based Multi-Task Framework
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