Yaochen Zhu (朱耀晨)

Publications

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 the Survey Track) | paper | slides

Surveys:

1. Knowledge Editing for Large Language Models: A Survey
   Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li
   ACM CSUR 2024 | paper

Conference Papers:

1. Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
   Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
   ICLR 2025 | paper | codes
2. Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems
   Yaochen Zhu, Chao Wan, Harald Steck, Dawen Liang, Yesu Feng, Nathan Kallus, Jundong Li
   WWW 2025 | paper | codes
   Work done when Yaochen was a machine learning research intern at Netflix Inc. (Summer'24)
3. Collaborative Diffusion Model for Recommender System
   Gyuseok Lee, Yaochen Zhu, Hwanjo Yu, Yao Zhou, Jundong Li
   WWW 2025 (Short Paper) | paper | codes
   Work done when Gyuseok was a research intern at UVA with me.
4. Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective
   Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li
   EMNLP 2024 (Findings) | paper | codes
5. 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
6. 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
7. Knowledge Graph-Enhanced Large Language Models via Path Selection
   Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li
   ACL 2024 (Findings) | paper | codes
8. 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).
   Work done when Yaochen was an applied research intern at Linkedin Inc (Summer'23).
9. Path-specific Counterfactual Fairness for Recommender Systems
   Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
   KDD 2023 | paper | codes
10. Mutually-regularized dual collaborative variational auto-encoder for recommendation systems
    Yaochen Zhu and Zhenzhong Chen
    WWW 2022 | paper | codes | slides
11. 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
12. 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. Global Graph Counterfactual Explanation: A Subgraph Mapping Approach
   Yinhan He, Wendy Zheng, Yaochen Zhu, Jing Ma, Saumitra Mishra, Natraj Raman, Ninghao Liu, Jundong Li
   TMLR, 2025. | paper | codes
2. Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
   Song Wang, Zhen Tan, Yaochen Zhu, Chuxu Zhang, Jundong Li
   TMLR, 2025. | paper | codes
3. Disentangling User Interest and Geographical Context for POI Recommendations
   Wenhui Meng, Jiayi Xie, Jing Yi, Yaochen Zhu,Zhenzhong Chen
   ACM TIST, 2025. | paper | codes
4. Deep causal reasoning for recommendations
   Yaochen Zhu, Jing Yi, Jiayi Xie, Zhenzhong Chen
   ACM TIST, 2024. | paper | codes
5. Variational bandwidth auto-encoder for hybrid recommender systems
   Yaochen Zhu and Zhenzhong Chen
   IEEE TKDE, 2022. | paper | codes
6. Cross-modal variational auto-encoder for micro-video background music recommendation
   Jing Yi, Yaochen Zhu, Jiayi Xie, Zhenzhong Chen
   IEEE TMM, 2021. | paper | codes
7. Micro-video popularity prediction via multimodal variational information bottleneck
   Jiayi Xie, Yaochen Zhu, Zhenzhong Chen
   IEEE TMM, 2021. | paper | codes
8. Affective video content analysis via multimodal deep quality embedding network
   Yaochen Zhu, Zhenzhong Chen, Feng Wu
   IEEE TAFFC, 2020. | paper | codes

Preprint:

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 | 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

Service

Awards