8 papers · 1 filter
IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications
Yiling Ma, Yilun Zhao, Sihong Wu +2
A research idea may be novel, coherent, and scientifically plausible, yet its proposed method may remain insufficiently specified for faithful implementation. We study the codifica…
ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation
Yiling Ma, Yilun Zhao, Sihong Wu +3
As LLMs are increasingly used for pre-submission self-review, there is growing demand for feedback that not only identifies weaknesses but also guides authors toward concrete revis…
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…
SciMDR: Advancing Scientific Multimodal Document Reasoning
Ziyu Chen, Yilun Zhao, Chengye Wang +3
Constructing scientific multimodal document reasoning datasets for foundation model training involves an inherent trade-off among scale, faithfulness, and realism. To address this…
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…
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…
Experience Retrieval-Augmentation with Electronic Health Records Enables Accurate Discharge QA
Justice Ou, Tinglin Huang, Yilun Zhao +3
To improve the reliability of Large Language Models (LLMs) in clinical applications, retrieval-augmented generation (RAG) is extensively applied to provide factual medical knowledg…