19 papers
HippoSpark: An On-Demand Experience System for LLM Reasoning
Jingyao Liu, Danling Meng, Chen Huang +5
Distilling historical trajectories into reusable experience to enhance future problem-solving has become a focal point of recent LLM research. However, existing methods predominant…
Unlocking Biological Workflows for Robust Protein-Text Question Answering: A Dual-Dimensional RAG Framework
Li Ding, Duanyu Feng, Chen Huang +4
Protein-Text Question Answering (QA) is crucial for interpreting biological sequences through natural language. The integration of Large Language Models (LLMs) with Retrieval-Augme…
Bilevel Optimization of Agent Skills via Monte Carlo Tree Search
Chenyi Huang, Haoting Zhang, Jingxu Xu +2
Agent \texttt{skills} are structured collections of instructions, tools, and supporting resources that help large language model (LLM) agents perform particular classes of tasks. E…
Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering
Weikang Zhang, Zimo Zhu, Zhichuan Yang +3
Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely on discrete prompt engineeri…
METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models
Pengfeng Li, Chen Huang, Chaoqun Hao +4
Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate this skill in fragmented setting…
METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues
Haofu Yang, Jiaji Liu, Chen Huang +3
Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose \ours, a method that leverages large langua…