Min Zeng 曾敏

I am Min Zeng, a Postdoctoral Research Associate at University of Minnesota , working with Prof. Rui Zhang . I received my Ph.D. in Electronic and Computer Engineering from HKUST , advised by Prof. Yike Guo , and my Master's degree in Computer Science and Engineering from Shanghai Jiao Tong University , advised by Prof. Yuan Luo .

Email · Google Scholar

I welcome collaborations. Feel free to reach out via email.

Research

My research focuses on enabling large language models (LLMs) to continuously learn and adapt to evolving tasks, data, and environments while retaining previously acquired knowledge, remaining efficient, reliable, and trustworthy.

Current Research Interests:

  • Continual / Lifelong Learning
  • Longitudinal Reasoning
  • AI for Healthcare

Selected Publications [Full List]

* Equal contribution.

Dirichlet Continual Learning

Dirichlet Continual Learning: Tackling Catastrophic Forgetting in NLP

Min Zeng, Haiqin Yang, Wei Xue, Qifeng Liu, Yike Guo

Conference on Uncertainty in Artificial Intelligence (UAI), 2024

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Sparse Adapter Fusion for Continual Learning

Sparse Adapter Fusion for Continual Learning in NLP

Min Zeng*, Xi Chen*, Haiqin Yang, Yike Guo

Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2026

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Task-Wrapped Continual Learning for Task-Oriented Dialogue Systems

Task-Wrapped Continual Learning for Task-Oriented Dialogue Systems

Min Zeng, Haiqin Yang, Xi Chen, Yike Guo

Findings of the Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL), 2025

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Prototype Conditioned Generative Replay for Continual Learning in NLP

Prototype Conditioned Generative Replay for Continual Learning in NLP

Xi Chen*, Min Zeng*

Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL), 2025

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Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation

Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation

Min Zeng, Yisen Wang, Yuan Luo

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019

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RHO: Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding

RHO: Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding

Ziwei Ji, Zihan Liu, Nayeon Lee, Tiezheng Yu, Bryan Wilie, Min Zeng, Pascale Fung

Findings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2023

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Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension

Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension

Holy Lovenia*, Bryan Wilie*, Willy Chung*, Min Zeng*, Samuel Cahyawijaya, Dan Su, Pascale Fung

Proceedings of the 7th Workshop on Representation Learning for NLP (RepL4NLP @ ACL), 2022

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Multimodal Artificial Intelligence Agents in Healthcare: A Scoping Review

Multimodal Artificial Intelligence Agents in Healthcare: A Scoping Review

Kai Yu, Shuang Zhou, Yu Hou, Yiran Song, Min Zeng, Fangqiao Tian, Jin Du, Wenya Xie, Biao Yin, You Chen, Feifan Liu, Jie Ding, Zirui Liu, Mingquan Lin, Rui Zhang

NPJ Digital Medicine (Nature Portfolio), 2026

Services

Conference Area Chair: ACL Rolling Review (ARR), January 2026

Conference Reviewers: ACL, EMNLP, NAACL, UAI, EACL

Journal Reviewers: IEEE TASLP, NPJ Digital Medicine, NPJ Health Systems

Academic Service: AMIA 2025 NLP Year-in-Review Volunteer