activity
20242026
most citedSciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis

14 citations · 24 across the 10 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

DISA: Offline Importance Sampling for Distribution-Matching LLM-RL

Shaobo Wang, Yujie Chen, Yafeng Sun +9

Modern reasoning agents are increasingly evaluated on their ability to generate multiple valid solution paths, plans, or tool-use traces for a given input. Standard reward-maximizi…

cs.LG2026

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents

Wei Shi, Ziheng Peng, Sihang Li +4

LLM agents exhibit a consistent tendency to over-call, invoking tools even in situations where none is needed. On the When2Call benchmark, six models from three families show high…

cs.LG2025

MolReasoner: Toward Effective and Interpretable Reasoning for Molecular LLMs

Guojiang Zhao, Zixiang Lu, Yutang Ge +13

Large Language Models (LLMs) have shown impressive performance across various domains, but their ability to perform molecular reasoning remains underexplored. Existing methods most…

cs.LG2025★ 3 cited

Intelligent System for Automated Molecular Patent Infringement Assessment

Yaorui Shi, Sihang Li, Taiyan Zhang +12

Automated drug discovery offers significant potential for accelerating the development of novel therapeutics by substituting labor-intensive human workflows with machine-driven pro…

cs.LG2024★ 2 cited

SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Sihang Li, Jin Huang, Jiaxi Zhuang +7

Scientific literature understanding is crucial for extracting targeted information and garnering insights, thereby significantly advancing scientific discovery. Despite the remarka…