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Jinyuan Li

李金源
Tianjin University (TJU)
jinyuanli@tju.edu.cn


About Me

I am a final-year master’s student at Tianjin University, under the mentorship of Prof. Gang Pan. Previously, I worked as a research intern at Baidu and explored multimodal document understanding. I am also fortunate to work with Prof. Jianfei Yu during my research journey.

My enthusiasm lies in exploring Multimodal Learning, Vision and Language. My recent series of work (MNER->GMNER->SMNER) explored how to unleash the potential capabilities of visual-language models in complex multimodal scenarios, how to build harmonious interaction and collaboration between multiple models, and how to construct image-text based knowledge augmentation methods in open-world scenarios. Additionally, I also maintain interest in several visual tasks (e.g., Blind Image Inpainting, Infrared and Visible Image Fusion).

I’m open to collaboration and discussions. Please feel free to contact me and explore possibilities together.

Research Interests

Vision and Language:

News🔥

Publications

  1. ACL
    Jinyuan Li, Han Li, Di Sun, Jiahao Wang, Wenkun Zhang, Zan Wang, Gang Pan
    Findings of the Association for Computational Linguistics (ACL) 2024, Bangkok, Thailand

  2. EMNLP
    Jinyuan Li, Han Li, Zhuo Pan, Di Sun, Jiahao Wang, Wenkun Zhang, Gang Pan
    Findings of the Association for Computational Linguistics (EMNLP) 2023, Singapore

  3. arxiv
    Jinyuan Li, Ziyan Li, Han Li, Jianfei Yu, Rui Xia, Di Sun, Gang Pan
    arxiv, 2024

  4. arxiv
    Jiahao Wang, Jinyuan Li, Gang Pan, Di Sun, Jiawan Zhang
    arxiv, 2024

  5. arxiv
    Yonglu Liu, Gang Pan, Jinyuan Li, Zhenjun Han, Jiahao Wang, Di Sun
    arxiv, 2024

Experience

Services

Conference Reviewer/Program Committee

Journal Reviewer

Teaching Assistant

Awards and Honors

Miscellaneous

When I’m not in research mode, I enjoy swimming (Swim one kilometer freestyle in less than 18 minutes) and violin (Fluent sight-reading skills). They have been with me for nearly twenty years. My favorite virtuoso is Ray Chen. His interpretation of the music always carries a distinct personal touch. I hope I can approach my research in the same way.

In the past, I demonstrated strong road cycling capabilities, maintaining a speed of 36 km/h for two hours. Additionally, I found being an anchor very engaging.