14 citations · 70 across the 73 of their papers we have counts for
7 papers · 2 filters
Small Language Models as Judges for Rubric-Based Reinforcement Learning
Fengyu Xie, Yilun Zhao, Bingsen Chen +2
Rubric-based reinforcement learning extends RL beyond tasks with exact answers or rule-based verifiers by scoring responses against instance-specific criteria. However, this makes…
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…
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…
MedTutor: A Retrieval-Augmented LLM System for Case-Based Medical Education
Dongsuk Jang, Ziyao Shangguan, Kyle Tegtmeyer +4
The learning process for medical residents presents significant challenges, demanding both the ability to interpret complex case reports and the rapid acquisition of accurate medic…
Patient-Similarity Cohort Reasoning in Clinical Text-to-SQL
Yifei Shen, Yilun Zhao, Justice Ou +2
Real-world clinical text-to-SQL requires reasoning over heterogeneous EHR tables, temporal windows, and patient-similarity cohorts to produce executable queries. We introduce CLINS…