All Stories

  1. Recommendation Unlearning via Influence Function
  2. Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
  3. GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting
  4. Large Language Models for Recommendation: Past, Present, and Future
  5. Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach
  6. Large Language Models are Learnable Planners for Long-Term Recommendation
  7. Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation
  8. The 2nd Workshop on Recommendation with Generative Models
  9. Large Language Models for Recommendation: Progresses and Future Directions
  10. LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting
  11. Large Language Models for Recommendation: Progresses and Future Directions
  12. The 1st Workshop on Recommendation with Generative Models
  13. Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework
  14. Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
  15. TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
  16. Causal Recommendation: Progresses and Future Directions
  17. Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation
  18. Towards Trustworthy Recommender System: A Faithful and Responsible Recommendation Perspective
  19. Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation
  20. Addressing Confounding Feature Issue for Causal Recommendation
  21. Accepted Tutorials at The Web Conference 2022
  22. Causal Intervention for Leveraging Popularity Bias in Recommendation
  23. How to Retrain Recommender System?