刘汉蒙（Hanmeng Liu）

1121 School of Computer Science and Technology

58 Renmin Avenue

Haikou 570228

Hainan, P.R. China

I’m a Natural Language Processing researcher at Hainan University.

I obtained my Ph.D. degree at Zhejiang University & Westlake University in 2024.

I was advised by Prof. Yue Zhang at WestlakeNLP Lab. As one of the first members of WestlakeNLP Lab, I designed the badge of the lab, cooperated with Prof Yue Zhang for the NLP MOOC.

After graduation, I joined Huawei as a senior engineer at the department of ICT.

My research interests are large language model reasoning, especially logical reasoning.

I have a BILIBILI channel. I’m planning to share more contents on LLM tutorials and AI podcasts.

Shoutout to my big bro — I couldn’t have started my PhD journey without him.

news

Apr 12, 2025	I left HUAWEI and joins Hainan University as an associate professor.

latest posts

Apr 15, 2025	大模型约束解码（Constrained decoding）与结构化输出

selected publications

LogiCoT: Logical Chain-of-Thought Instruction Tuning

Hanmeng Liu, Zhiyang Teng, Leyang Cui, and 3 more authors

In Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

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Generative Pre-trained Transformer 4 (GPT-4) demonstrates impressive chain-of-thought reasoning ability. Recent work on self-instruction tuning, such as Alpaca, has focused on enhancing the general proficiency of models. These instructions enable the model to achieve performance comparable to GPT-3.5 on general tasks like open-domain text generation and paraphrasing. However, they fall short of helping the model handle complex reasoning tasks. To bridge the gap, this paper presents LogiCoT, a new instruction-tuning dataset for Logical Chain-of-Thought reasoning with GPT-4. We elaborate on the process of harvesting instructions for prompting GPT-4 to generate chain-of-thought rationales. LogiCoT serves as an instruction set for teaching models of logical reasoning and elicits general reasoning skills.
@inproceedings{liu2023logicot, title = {LogiCoT: Logical Chain-of-Thought Instruction Tuning}, author = {Liu, Hanmeng and Teng, Zhiyang and Cui, Leyang and Zhang, Chaoli and Zhou, Qiji and Zhang, Yue}, booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2023}, pages = {2908--2921}, year = {2023}, }