2 citations · 5 across the 18 of their papers we have counts for
47 papers · 1 filter
Measuring the Gap Between Human and LLM Research Ideas
Ziyu Chen, Yilun Zhao, Arman Cohan
LLMs are increasingly used to brainstorm research ideas, but existing evaluations mostly judge individual ideas by novelty, feasibility, or expert preference. We instead ask: how f…
MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworks
Yanjun Shao, Xiangru Tang, Jiwoong Sohn +10
Complex medical reasoning requires integrating heterogeneous clinical evidence across multiple inference steps. Large language models (LLMs) now approach this through two routes: i…
Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning
Alan Li, Yixin Liu, Arpan Sarkar +2
Scientific problem solving poses unique challenges for LLMs, requiring both deep domain knowledge and the ability to apply such knowledge through complex reasoning. While automated…
Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems
Yilun Zhao, Jinbiao Wei, Tingyu Song +3
Reasoning-intensive retrieval aims to surface evidence that supports downstream reasoning rather than merely matching topical similarity. This capability is increasingly important…
Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future
Sihong Wu, Owen Jiang, Yilun Zhao +5
Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLM…
RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation
Sihong Wu, Yiling Ma, Yilun Zhao +4
Large language models (LLMs) are increasingly used across the scientific workflow, including to draft peer-review reports. However, many AI-generated reviews are superficial and in…