9 papers
CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG
Jianghan Shen, Siqi Luo, Xinyu Cheng +6
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for training agentic retrieval-augmented generation (RAG) systems from outcome-only superv…
Can LLMs Predict Polymer Physics Just by Reading Synthesis and Processing Prose?
Yuchu Liu, Rui Zhu, Jingwei Xiong +1
Can large language models predict physical and mechanical polymer properties simply by reading unstructured scientific prose? Polymer performance is rarely determined by chemical s…
Hey, That's My Data! Token-Only Dataset Inference in Large Language Models
Chen Xiong, Zihao Wang, Rui Zhu +4
Large Language Models (LLMs) rely on massive training datasets, often including proprietary data, which raises concerns about unauthorized usage and copyright infringement. Existin…
MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline
Jiyao Liu, Jianghan Shen, Sida Song +19
Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medicine, developing clinical guid…
"Excuse me, may I say something..." CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations
Yang Wu, Jinhong Yu, Jingwei Xiong +2
The integration of Large Language Models (LLMs) into scientific workflows presents exciting opportunities to accelerate biomedical discovery. However, the reactive nature of LLMs,…
KEDRec-LM: A Knowledge-distilled Explainable Drug Recommendation Large Language Model
Kai Zhang, Rui Zhu, Shutian Ma +4
Drug discovery is a critical task in biomedical natural language processing (NLP), yet explainable drug discovery remains underexplored. Meanwhile, large language models (LLMs) hav…