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Hanzhu Chen

PhD Student


hanzhuchen@miralab.ai, chenhz@mail.ustc.edu.cn

Interests

  • Large Language Model
  • Knowledge Graph
  • Data Synthesis

Education

  • B.S., Computer Science and Technology, 2021, 2021

    Southwest University

About me

I am currently a PhD student in USTC. My advisor is Prof. Jie Wang, who leads the MIRA Lab. My research interests include large language model, knowledge graph, and data synthesis.

Awards

  • Excellent Interns, Noah’s Ark Lab (5/400+)
  • First place among university teams in KDD Cup 2022
  • National Encouragement Scholarship 2019

Experience

  • Intern at Alibaba DAMO Academy, 2023/07 - 2024/07
  • Intern at Noah’s Ark Lab, Huawei Technologies, 2024/10 -

Publications

Hanzhu Chen, Lin Yang, Jie Wang, Junhao Yan, Zhe Wang, Xize Liang, Jianye Hao. Latent-Guided Reasoning: Empowering Small LLMs with Large-Model Thinking. ICLR 2026.

Xize Liang, Lin Yang, Jie Wang, Rui Liu, Yang Lu, Jinliang Zeng, Hanzhu Chen, Dong Li, Jianye Hao. Boosting Multi-Domain Reasoning of LLMs via Curvature-Guided Policy Optimization. ICLR 2026.

Xiaoqi Ni, Jie Wang, Lin Yang, Yiyang Lu, Hanzhu Chen, Rui Liu, Jianye Hao. Following the Navigation: Enhancing Small Language Models Contextual Reasoning with LLM Guidance. ICLR 2026.

Zehao Wang, Lin Yang, Jie Wang, Kehan Wang, Hanzhu Chen, Bin Wang, Jianye Hao, Defu Lian, Bin Li, Enhong Chen. LogicTree: Improving Complex Reasoning of LLMs via Instantiated Multi-step Synthetic Logical Data. NeurIPS 2025.

Poster

Yue Shen, Jie Wang, Zhe Wang, Zhihao Shi, Hanzhu Chen, Zheng Wang, Yukang Jiang, Xiaopu Wang, Chuandong Cheng, Xueqin Wang, Hongtu Zhu, Jieping Ye. CATI: A medical context-enhanced framework for diagnosis code assignment in the UK Biobank study. AI in Medicine.

Xize Liang, Chao Chen, Shuang Qiu, Jie Wang, Yue Wu, Zhihang Fu, Hanzhu Chen, Feng Wu, Jieping Ye. ROPO: Robust Preference Optimization for Large Language Models. ICML 2025.

Xize Liang, Lin Yang, Jie Wang, Yiyang Lu, Runyu Wu, Hanzhu Chen, Jianye Hao. Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples. ICML 2025.

Hanzhu Chen, Xu Shen, Jie Wang, Zehao Wang, Qitan Lv, Junjie He, Rong Wu, Feng Wu, Jieping Ye. Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models. ICLR 2025.

Jian Luo, Jie Wang, Hong Wang, huanshuo dong, Zijie Geng, Hanzhu Chen, Yufei Kuang. Neural Krylov Iteration for Accelerating Linear System Solving. NeurIPS 2024.

Zhihao Shi, Jie Wang, Fanghua Lu, Hanzhu Chen, Defu Lian, Zheng Wang, Jieping Ye, Feng Wu. Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias. TPAMI.

Hanzhu Chen, Xu Shen, Qitan Lv, Jie Wang, Xiaoqi Ni, Jieping Ye. SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graph. ACL 2024.

Qitan Lv, Jie Wang, Hanzhu Chen, Bin Li, Yongdong Zhang, Feng Wu. Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models. ICML 2024.

Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen. Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction. NeurIPS 2023.

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