Zhuangzhuang He

I am a final-year master's student advised by Prof. Le Wu and Prof. Richang Hong in the Computer Science department at the Hefei University of Technology. Prior to joining HFUT in 2022, I earned my B.S. degree in Computer Science from Anhui Agricultural University.

And many thanks to Prof. Min Zhang and Prof. Peijie Sun for hosting my research visit to the Information Retrieval Group at Tsinghua University during the summer of 2023.

I have all in LLM. My research interests covers a wide range of topics related to large language models, information retrieval:

  • Large Language Model: Reasoning, Agent;
  • LLM Applications: LLM for science.
I firmly believe that LLM are the most powerful tool for personal enhancement, and I am dedicated to making LLM stronger and faster. Wechat: Stay-Aliving.

心似白云常自在， 亦如流水任东西。

Email  /  Google Scholar  /  Github  /  Twitter  

Education

M.S.             2022 - 2025 (expected)
                      Computer Science and Technology, Hefei University of Technology (HFUT)
                      M.S. in Computer Science and Technology

B.S.              2018 - 2022
                      Computer Science and Technology, Anhui Agricultural University (AHAU)
                      B.S. in Computer Science and Technology
Papers

[1] Double Correction Framework for Denoising Recommendation [Code]
Zhuangzhuang He*, Yifan Wang*, Yonghui Yang, Peijie Sun, Le Wu, Haoyue Bai, Jinqi Gong, Richang Hong, Min Zhang
KDD 2024, Oral Presentation.
[2] Graph Bottlenecked Social Recommendation [Code]
Yonghui Yang, Le Wu, Zihan Wang, Zhuangzhuang He, Richang Hong, Meng Wang
KDD 2024, Oral Presentation.
[3] Multimodality Invariant Learning for Multimedia-Based New Item Recommendation [Code]
Haoyue Bai, Le Wu, Min Hou, Miaomiao Cai, Zhuangzhuang He, Yuyang Zhou, Richang Hong, Meng Wang
SIGIR 2024
[4] An Ensemble View on Denoising Recommendation [Code]
Weipu Chen*, Zhuangzhuang He*, Fei Liu
ICASSP 2025
[5] It is Never Too Late to Mend: Separate Learning for Multimedia Recommendation [Code]
Zhuangzhuang He, Zihan Wang, Yonghui Yang, Haoyue Bai, Le Wu
[6] Weakly Supervised Spam Review Detection with Graph Markov Network
Zhuangzhuang He, Le Wu, Peijie Sun, Yonghui Yang, Haoyue Bai, Jinqi Gong, Richang Hong
GitHub Project

⭐️ GitHub Stars   🚀 Awesome-RL-based-LLM-Reasoning
A curated list of resources for Reinforcement Learning (RL) based Large Language Model (LLM) reasoning.

⭐️ GitHub Stars   🍳 The Simplest LLM-based Agent
Single-agent and multi-agent communication, implementing functions such as memory, planning, and function calling.

🐉 Camel-Ai|Loong (In Progress)
Reasoning in various domains Long CoT dataset.

Experiences
Department of Computer Science, University of Rochester, NYC, USA
Research Assistant • Oct. 2023 to May 2024
Graph OOD Generalization
Advisor: Prof. Jian Kang and Dr. Jun Wu (UIUC)
Information Retrieval Group, Tsinghua University, Beijing, China
Visting Student • Apr. 2023 to Aug 2023
Denoising Recommendation
Advisor: Prof. Min Zhang and Prof. Peijie Sun
Data Mining Group, Hefet University of Technology, Hefei, China
Research Assistant • Sep. 2022 to Jun. 2025
Misinformation and Large language model
Collaborator: Dr. Yonghui Yang (NUS) and Dr. Haoyue Bai (ASU)
Honors & Awards

[2024] China National Scholarship (Top 1%)
[2022] The HuBingXueZi Scholarship in HFUT (Top 3%)
[2022] Outstanding Graduates in Anhui Province (Top 1%)
[2019/2020/2021] Merit Student in AHAU (Top 5%)
[2019/2020/2021] The First Prize Scholarship in AHAU (Top 5%)
Professional Services

Journal Reviewer: IEEE TKDE, IEEE TNNLS
Conference Reviewer: ICLR 2025, KDD 2025, KDD 2024, MM 2024, WWW 2025