Tutorials:

Tutorials:

1. Causal Inference with Latent Variables: Recent Advances and Future Perspectives
   Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li
   KDD 2024 (Accepted to Survey Track) | paper

Surveys:

1. Usable XAI: 10 strategies towards exploiting explainability in the LLM era
   Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Jundong Li, Mengnan Du, Ninghao Liu
   ArXiv 2024 | paper

2. Knowledge Editing for Large Language Models: A Survey
   Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li
   ACM CSUR | paper

Conference Papers:

1. Understanding and Modeling Job Marketplace with Pretrained Language Models
   Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li
   CIKM 2024 | paper | codes

2. Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations
   Linxin Guo, Yaochen Zhu, Min Gao, Yinghui Tao, Junliang Yu, Jundong Li
   KDD 2024 | paper | codes

3. Knowledge Graph-Enhanced Large Language Models via Path Selection
   Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li
   ACL 2024 (Findings) | paper | codes

4. Collaborative Large Language Model for Recommender Systems
   Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
   WWW 2024 | paper | codes
   Invited Poster Presentation at 2024 Netflix Workshop on Personalization, Recommendation and Search (PRS).

5. Path-specific Counterfactual Fairness for Recommender Systems
   Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
   KDD 2023 | paper | codes

6. Mutually-regularized dual collaborative variational auto-encoder for recommendation systems
   Yaochen Zhu and Zhenzhong Chen
   WWW 2022 | paper | codes | slides

7. A multimodal variational encoder-decoder framework for micro-video popularity prediction
   Jiayi Xie, Yaochen Zhu, …, Zhenzhong Chen (Short paper, * for equal contribution)
   WWW 2020 | paper | codes

8. Multimodal deep denoising framework for affective video content analysis
   Yaochen Zhu, Zhenzhong Chen, Feng Wu
   ACM MM 2019 | paper | Oral | image1 | image2 | image3 | image4

Journal Papers:

1. Deep causal reasoning for recommendations
   Yaochen Zhu, Jing Yi, Jiayi Xie, Zhenzhong Chen
   ACM TIST, 2022. | paper | codes

2. Variational bandwidth auto-encoder for hybrid recommender systems
   Yaochen Zhu and Zhenzhong Chen
   IEEE TKDE, 2022. | paper | codes

3. Cross-modal variational auto-encoder for micro-video background music recommendation
   Jing Yi, Yaochen Zhu, Jiayi Xie, Zhenzhong Chen
   IEEE TMM, 2021. | paper | codes

4. Micro-video popularity prediction via multimodal variational information bottleneck
   Jiayi Xie, Yaochen Zhu, Zhenzhong Chen
   IEEE TMM, 2021. | paper | codes

5. Affective video content analysis via multimodal deep quality embedding network
   Yaochen Zhu, Zhenzhong Chen, Feng Wu
   IEEE TAFFC, 2020. | paper | codes

Book Chapters:

1. Causal Inference in Recommender Systems: A Survey of Strategies for Bias Mitigation, Explanation, and Generalization
   Yaochen Zhu, Jing Ma, Jundong Li
   Chapter 10, Machine Learning for Causal Inference, Springer | paper