Tianshi Zheng 郑天石 Stone
Bibliography
Hello there!
I’m a Ph.D. candidate in Computer Science at the Hong Kong University of Science and Technology (HKUST) starting from 2024, advised by Prof. Yangqiu Song. I’m also a research intern at NVIDIA AI Technology Center. Prior to that, I obtained two bachelor’s degrees in Computer Science and General Business Management from the Dual Degree Program at the same institution with the highest distinction.
News
- Nov 2025: One research paper accepted to TMLR!
- Oct 2025: Successfully passed my PhD Qualification Defense! Thanks to my committee members Junxian and May!
- Oct 2025: Our latest work on scientific discovery: NewtonBench has been published, with benchmarking code released in github: NewtonBench .
- Aug 2025: Two research papers accepted to EMNLP 2025 Main Conference!
- May 2025: Our survey paper on Large Language Models in Scientific Discovery has been published, with an awesome github repository: Awesome-LLM-Scientific-Discovery . We welcome community contributions through pull requests!
- May 2025: Four research papers accepted to ACL 2025!
Research Interests
I am generally interested in Machine Learning and Natural Language Processing.
RI1. Logical Inference Towards Explanatory Hypothesis from Observations.
It naturally bridges:
- Abductive Reasoning: Explanatory Hypothesis Generation (LogiDynamics, AbductiveKGR, Controllable AKGR)
- Inductive Reasoning: Learning from Contextual Instances (The Curse of CoT, Robust Rule Induction, Legal Rule Induction)
- Deductive Reasoning: Entailment Verification with Uncertainty (FOL-Entailment)
RI2. AI-Driven Autonomous Scientific Discovery and Research [LLM-SD Survey].
My focus is on accelerating the autonomy of AI agents, in tasks ranging from general scientific discovery to machine learning research.
- Self-Improving / Self-Evolving Optimization for Autonomous R&D
- Interactive Environments for Generalizable Scientific Discovery with LLM Agents (NewtonBench)
I’ve been also working on complex logical reasoning under diverse modalities and scenarios (SQE, CLR-Fact, KnowShiftQA).
Selected Papers
NewtonBench: Benchmarking Generalizable Scientific Law Discovery in LLM Agents.
Tianshi Zheng*, Kelvin Tam*, Newt Nguyen*, Baixuan Xu, Zhaowei Wang, Jiayang Cheng, Hong Ting Tsang, Weiqi Wang, Jiaxin Bai, Tianqing Fang, Yangqiu Song, Ginny Y Wong, Simon See.
ArXiv Preprint [pdf], [code]The Curse of CoT: On the Limitations of Chain-of-Thought in In-Context Learning.
Tianshi Zheng*, Yixiang Chen*, Chengxi Li*, Chunyang Li, Qing Zong, Haochen Shi, Baixuan Xu, Yangqiu Song, Ginny Y Wong, Simon See.
TMLR 2025 [pdf], [code]From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery.
Tianshi Zheng, Zheye Deng, Hong Ting Tsang, Weiqi Wang, Jiaxin Bai, Zihao Wang, Yangqiu Song.
EMNLP 2025 Main Conference [pdf], [code]LogiDynamics: Unraveling the Dynamics of Logical Inference in Large Language Model Reasoning.
Tianshi Zheng, Jiayang Cheng, Chunyang Li, Haochen Shi, Zihao Wang, Jiaxin Bai, Yangqiu Song, Ginny Y Wong, Simon See.
EMNLP 2025 Main Conference [pdf], [code]Enhancing Transformers for Generalizable First-Order Logical Entailment.
Tianshi Zheng*, Jiazheng Wang*, Zihao Wang, Jiaxin Bai, Hang Yin, Zheye Deng, Yangqiu Song, Jianxin Li.
ACL 2025 Main Conference [pdf], [code]KnowShiftQA: How Robust are RAG Systems when Textbook Knowledge Shifts in K-12 Education?
Tianshi Zheng*, Weihan Li*, Jiaxin Bai, Weiqi Wang, Yangqiu Song.
ACL 2025 Main Conference [pdf], [code]
Awards
- Hong Kong PhD Fellowship 2024
- HKUST RedBird PhD Scholarship 2024
- HKUST Academic Achievement Medal (~top 1% graduate)
- HKUST Dean's Lists (7 semesters)
Academic Service
Conference Reviewer: ACL Rolling Review (2023, 2024, 2025), EMNLP 2023, KDD 2024, NLPCC 2024, ICLR 2025, COLM 2025