All Stories

  1. Self-supervised Causal Effects Estimation
  2. Causal Abstraction Learning for Multi-Modal Grounded Planning
  3. HiBrain: Hierarchical Prototype Learning on Multimodal Brain Graphs for Stage-Aware Biomarker Discovery
  4. ExODRec: An Explainable Framework for Outlier Detection Model Recommendation
  5. Verifiable User Simulation for Search and Recommendation Systems
  6. Task-Aware Automated User Profile Generation for Recommendation Simulation Using Large Language Models
  7. Mitigating Bias in Large Language Model Based Question Answering through Causal Front Door Prompting
  8. Energy-Efficient Training-Free Zero-Inflation Correction for Rainfall Forecasting with Time-Series Foundation Models
  9. When to Invoke: Refining LLM Fairness with Toxicity Assessment
  10. When to Trust: A Causality-Aware Calibration Framework for Accurate Knowledge Graph Retrieval-Augmented Generation
  11. FairGE: Fairness-Aware Graph Encoding in Incomplete Social Networks
  12. Harnessing LLM for Noise-Robust Cognitive Diagnosis in Web-Based Intelligent Education Systems
  13. MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation
  14. Unbiased Reasoning for Knowledge-Intensive Tasks in Large Language Models via Conditional Front-Door Adjustment
  15. Revisiting Pre-processing Group Fairness: A Modular Benchmarking Framework
  16. Temporal-Aware User Behaviour Simulation with Large Language Models for Recommender Systems
  17. FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Prediction
  18. PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation
  19. Towards Better Evaluation of Recommendation Algorithms with Bi-directional Item Response Theory
  20. Testing fairness measures in machine learning using an approach for designing tests in education.
  21. Off-policy Evaluation for Multiple Actions in the Presence of Unobserved Confounders