Meng Fang
I am an Assistant Professor in AI at University of Liverpool. I'm also a visiting (assistant) professor at Eindhoven University of Technology (TU/e).
I received my Ph.D. from University of Technology Sydney, advised by Prof. Dacheng Tao, and then worked as a postdoc with Prof. Trevor Cohn at the University of Melbourne NLP group.
I had been a research scientist / intern at Tencent Robotics X / AI, CSIRO and Microsoft Research Asia before.
My research focuses on auto agents or systems capable of human-like language understanding, reasoning, and decision-making. My main areas include NLP and RL.
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News
- 5 papers accepted to ICLR 2025 with research spanning topics in Large Language Models and RL. Congratulations to our students and collaborators.
- 2 papers accepted to ICLR 2024 and one of them is spotlight. Congratulations to our students and collaborators.
- Looking for motivated prospective students working with us. Please contact me to discuss potential topics and PhD opportunites.
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Projects
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Text-based games
TL;DR: We consider language understanding and reasoning for agents in text-based games.
Keywords: responsible AI, knowledge graphs, attention, RL, hierarchical RL.
[project page]
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Conversational AI
TL;DR: We consider chatbots for dialogue generation and reasoning.
Keywords: Language generation, persona.
[project page]
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Question & Answering
TL;DR: We consider the reasoning process for question and answering problems.
Keywords: Retrieval-augmented generation, open domain, knowledge graphs, graph neural networks
[project page]
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Reinforcement learning
TL;DR: We propose new agents and environments for robotics and Game AI.
Keywords: sparse/delayed rewards, sample efficient, multi-goal RL, continual learning.
[project page]
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Publications
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Selected: (Full publication list)
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Monte Carlo Planning with Large Language Model for Text-Based Game Agents
Zijing Shi, Meng Fang, Ling Chen
ICLR 2025 [Project]
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RuAG: Learned-rule-augmented Generation for Large Language Models
Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
ICLR 2025
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HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents
Tristan Tomilin, Meng Fang, Mykola Pechenizkiy
ICLR 2025 [Project]
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Towards Empowerment Gain through Causal Structure Learning in Model-Based RL
Hongye Cao, Fan Feng, Meng Fang, Shaokang Dong, Tianpei Yang, Jing Huo, Yang Gao
ICLR 2025
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Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
Jiawei Xu, Rui Yang, Shuang Qiu, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han
ICLR 2025 [Code]
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Self Data Augmentation for Open Domain Question Answering
Qin Zhang, Mengqi Zheng, Shangsi Chen, Han Liu, Meng Fang
ACM Transactions on Information Systems 2025
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Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies
Zirui Song, Guangxian Ouyang, Meng Fang, Hongbin Na, Zijing Shi, Zhenhao Chen, Yujie Fu, Zeyu Zhang, Shiyu Jiang, Miao Fang, Ling Chen, Xiuying Chen
NAACL 2025
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MTPChat: A Multimodal Time-Aware Persona Dataset for Conversational Agents
Wanqi Yang, Yanda Li, Meng Fang, Ling Chen
NAACL 2025 (Findings)
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Understanding, Rehearsing, and Introspecting: Learn a Policy from Textual Tutorial Books in Football Games
Xiong-Hui Chen, Ziyan Wang, Yali Du, Shengyi Jiang, Meng Fang, Yang Yu, Jun Wang
NeurIPS 2024 Oral
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Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf
Xuanfa Jin, Ziyan Wang, Yali Du, Meng Fang, Haifeng Zhang, Jun Wang
NeurIPS 2024
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RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering
Zihan Zhang, Meng Fang, Ling Chen
In ACL 2024 (Findings) [Code]
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More than Minorities and Majorities: Understanding Multilateral Bias in Language Generation
Jiaxu Zhao, Zijing Shi, Yitong Li, Yulong Pei, Ling Chen, Meng Fang, Mykola Pechenizkiy
In ACL 2024 (Findings)
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Large Language Models Are Neurosymbolic Reasoners
Meng Fang*, Shilong Deng*, Yudi Zhang*, Zijing Shi, Ling Chen, Mykola Pechenizkiy, Jun Wang
In AAAI 2024 [Code]
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MedINST: Meta Dataset of Biomedical Instructions
Wenhan Han, Meng Fang, Zihan Zhang, Yu Yin, Zirui Song, Ling Chen, Mykola Pechenizkiy, Qingyu Chen
EMNLP 2024 Findings [Code]
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Acknowledgements
I would like to thank all my collaborators, interns and students.
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