10 papers
Thinking with Visual Grounding
Junkai Zhang, Yihe Deng, Kai-Wei Chang +1
Visual thinking should not only sound right; it should show its evidence. While recent vision-language models (VLMs) can produce natural-language reasoning traces, these traces oft…
Enhancing LLM Safety Through a Theoretical Minimax Game Lens
Yihe Deng, Yu Yang, Junkai Zhang +2
The rapid advancement of large language models (LLMs) necessitates effective mechanisms to ensure their responsible deployment by accurately distinguishing unsafe content from beni…
MatSciBench: Benchmarking the Reasoning Ability of Large Language Models in Materials Science
Junkai Zhang, Jingru Gan, Xiaoxuan Wang +8
Large Language Models have shown strong scientific reasoning ability, but their performance on materials science problems remains less studied. To fill this gap, we introduce MatSc…
METASYMBO: Multi-Agent Language-Guided Metamaterial Discovery via Symbolic Latent Evolution
Jianpeng Chen, Wangzhi Zhan, Dongqi Fu +5
Metamaterial discovery seeks microstructured materials whose geometry induces targeted mechanical behavior. Existing inverse-design methods can efficiently generate candidates, but…
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics
Lianhao Zhou, Hongyi Ling, Cong Fu +14
Computing has long served as a cornerstone of scientific discovery. Recently, a paradigm shift has emerged with the rise of large language models (LLMs), introducing autonomous sys…
Chasing the Tail: Effective Rubric-based Reward Modeling for Large Language Model Post-Training
Junkai Zhang, Zihao Wang, Lin Gui +7
Reinforcement fine-tuning (RFT) often suffers from reward over-optimization, where a policy model hacks the reward signals to achieve high scores while producing low-quality output…