“Hundred Talent” Research Fellow
ZLST Lab · College of Computer Science and Technology · Zhejiang University
I am a “Hundred Talent” Research Fellow at the ZLST Lab in the College of Computer Science and Technology, Zhejiang University. I received my Ph.D. from Zhejiang University (advised by Prof. Chun Chen) and worked as a postdoctoral researcher at USTC (advised by Prof. Xiangnan He). My research focuses on recommender systems, large language models, and AI agents. I have published over 80 papers in top conferences and journals. My recent awards include the Outstanding Paper Award at ACL 2026, the Best Paper Award at WSDM 2025, and the Best Paper Honourable Mention at SIGIR 2023.
Prospective students: I am looking for self-motivated master’s and Ph.D. students. If you are interested in these topics, please email me your CV.
Self-evolving AI systems deployed in industry
Learning from industrial iteration histories to propose effective evolution directions and autonomously improve deployed AI systems.
ACL 2026 Outstanding Paper Award
Revisiting entropy interventions through the lens of entropy change in reinforcement learning with verifiable rewards.
WSDM 2025 Best Paper Award
Explaining popularity-bias amplification through spectral analysis and examining how to mitigate it in recommendation.
SIGIR 2023 Best Paper Honorable Mention
Addressing the rich-get-richer effect of offline reinforcement learning to improve interactive recommendation.
Bias Survey · ESI Hot Paper · 1,600+ citations
A systematic overview of recommendation biases, debiasing techniques, and directions toward more trustworthy recommender systems.
Outstanding Paper Award at ACL 2026 for our work on entropy interventions in RLVR.
2 papers accepted at KDD 2026 on recommendation scaling and LLMs for graphs.
2 papers accepted at ECML PKDD 2026 on LLM-based recommendation and model editing.
2 main-conference papers accepted at ACL 2026 on agent creation and LLM reinforcement learning.
3 papers accepted at SIGIR 2026 on LLM-based and generative recommendation.
1 paper accepted at ICLR 2026 on LLM reasoning.
4 papers accepted at WWW 2026 on LLM-enhanced recommendation, top-k optimization, and ranking-aware transformers.
1 benchmark paper accepted at KDD 2026 on GUI agent robustness.
4 papers accepted at NeurIPS 2025 on LLM-enhanced recommendation, graph learning, and causal inference.
1 paper accepted at ACM TOIS on LLMs for denoising sequential recommendation.
1 paper accepted at KDD 2025 on NDCG optimization.
1 paper accepted at SIGIR 2025 on LLM-based recommendation.
Best Paper Award at WSDM 2025 for our spectral analysis of popularity bias.
2 papers accepted at WWW 2025 on ranking transformers and graph structure learning.
1 paper accepted at AAAI 2025 on recommendation loss.
3 papers accepted at WSDM 2025 on popularity bias, graph transformers, and causal inference.
1 paper accepted at NeurIPS 2024 on recommendation loss.
1 survey accepted at ACM Computing Surveys on deep clustering.
2 papers accepted at RecSys 2024 on LLM-based recommendation.
2 papers accepted at CIKM 2024 on cross-domain recommendation and knowledge graph embedding.
1 paper accepted at ACM TOIS on recommendation debiasing.
2 papers accepted at SIGIR 2024 on graph-based and interactive recommendation.
1 paper accepted at WWW 2024 on robust recommendation.
1 paper accepted at ACM TOIS on recommendation loss.
2 papers accepted at ICDE 2024 on graph queries and recommendation loss.
2 papers accepted at NeurIPS 2023 on contrastive learning and graph structure learning.
2 papers accepted at CIKM 2023 on recommendation debiasing and graph structure learning.
Best Paper Honorable Mention at SIGIR 2023 for our work on offline reinforcement learning in interactive recommendation.
1 paper accepted at IJCAI 2023 on recommendation debiasing.
1 paper accepted at ACM TOIS on causal interactive recommendation.
2 papers accepted at SIGIR 2023 on debiasing interactive recommendation and robust sequential recommendation.
2 papers accepted at WWW 2023 on adaptive temperature and negative sampling for recommendation.
1 paper accepted at AAAI 2023 on information propagation.
1 paper accepted at IEEE TKDE on dynamic popularity bias.
1 paper accepted at WSDM 2023 on fair knowledge distillation.
2 papers accepted at CIKM 2022 on recommendation datasets.
1 survey accepted at ACM TOIS on recommendation debiasing.
1 paper accepted at WWW 2022 on hypergraph-based personalized search.
Updated our recommendation debiasing survey with causal explanations and recent debiasing methods.
1 paper accepted at CIKM 2021 on disentangled knowledge graph representation learning.
1 paper accepted at ICCV 2021 on graph-based knowledge distillation.
1 paper accepted at IEEE TKDE on sampling for recommendation.
1 tutorial accepted at RecSys 2021 on bias and debiasing in recommendation.
1 paper accepted at KDD 2021 on causal inference for recommendation debiasing.
1 paper accepted at SIGIR 2021 on a universal debiasing framework for recommendation.
1 paper accepted at ACM TOIS on sampling for recommendation.
1 paper accepted at WWW 2021 on the equivalence of graph convolutional networks and label propagation.
1 tutorial accepted at WWW 2021 on bias and debiasing in recommendation.
2 papers accepted at AAAI 2020 on unbiased recommendation and graph embedding.
Zhejiang University
ZLST Lab · College of Computer Science and Technology
University of Science and Technology of China
Advisor: Prof. Xiangnan He
Zhejiang University
Advisor: Prof. Chun Chen
Zhejiang University
Advisor: Prof. Chun Chen
University of Electronic Science and Technology of China
Rethinking Entropy Interventions in RLVR: An Entropy Change Perspective
How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective
Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation
