Published over 20 papers in top conferences and international journals including ACL, EMNLP, SIGIR, MM, CIKM, TALLIP, IPM, ToMM, and TMM. Specific publications include 'SeaPO: Strategic Error Amplification for Robust Preference Optimization of Large Language Models' (EMNLP 2025), 'APT: Improving Specialist LLM Performance with Weakness Case Acquisition and Iterative Preference Training' (ACL 2025), 'CommonIT: Commonality-Aware Instruction Tuning for Large Language Models via Data Partitions' (EMNLP 2024), etc.
Research Experience
Involved in multiple research projects, published numerous papers in areas such as multimodal learning, knowledge distillation, and image-text retrieval.
Education
Third-year Ph.D. candidate at the School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), co-advised by Min Zhang and Xuebo Liu.
Background
Research interests include NLP, large language models (LLMs), and knowledge distillation (KD). Long-term research goal is to build socially intelligent embodied agents with the ability to perceive and engage in multimodal human communication. Research focuses on: 1) fundamentals of multimodal learning, specifically the representation, translation, fusion, and alignment of heterogeneous data sources; 2) human-centered language and vision and their applications; 3) real-world deployment efficiency of LLMs.
Miscellany
Personal interests include research in areas such as multimodal learning, knowledge distillation, and image-text retrieval.