6 papers
Grounding LLMs in Scientific Discovery via Embodied Actions
Bo Zhang, Jinfeng Zhou, Yuxuan Chen +3
Large Language Models (LLMs) have shown significant potential in scientific discovery but struggle to bridge the gap between theoretical reasoning and verifiable physical simulatio…
Towards Exception Safety Code Generation with Intermediate Representation Agents Framework
Xuanming Zhang, Yuxuan Chen, Yuan Yuan +1
Large Language Models (LLMs) often struggle with robust exception handling in generated code, leading to fragile programs that are prone to runtime errors. We propose Seeker, a nov…
MAGI: Multi-Agent Guided Interview for Psychiatric Assessment
Guanqun Bi, Zhuang Chen, Zhoufu Liu +9
Automating structured clinical interviews could revolutionize mental healthcare accessibility, yet existing large language models (LLMs) approaches fail to align with psychiatric d…
Crisp: Cognitive Restructuring of Negative Thoughts through Multi-turn Supportive Dialogues
Jinfeng Zhou, Yuxuan Chen, Jianing Yin +9
Cognitive Restructuring (CR) is a psychotherapeutic process aimed at identifying and restructuring an individual's negative thoughts, arising from mental health challenges, into mo…
CharacterBench: Benchmarking Character Customization of Large Language Models
Jinfeng Zhou, Yongkang Huang, Bosi Wen +13
Character-based dialogue (aka role-playing) enables users to freely customize characters for interaction, which often relies on LLMs, raising the need to evaluate LLMs' character c…
Seeker: Towards Exception Safety Code Generation with Intermediate Language Agents Framework
Xuanming Zhang, Yuxuan Chen, Yiming Zheng +3
In real world software development, improper or missing exception handling can severely impact the robustness and reliability of code. Exception handling mechanisms require develop…