activity
20242026
most citedFocus Directions Make Your Language Models Pay More Attention to Relevant Contexts

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Beyond Scalar Scores: Exploring LLM-based Metrics for Clinical Significance Evaluation in Radiology Reports

Qingyu Lu, Ruochen Li, Liang Ding +3

Reliable evaluation of generated radiology reports requires strict clinical accuracy, as omitted critical findings or mischaracterized radiographic observations can directly affect…

cs.CL2026

SurgGoal: Rethinking Surgical Planning Evaluation via Goal-Satisfiability

Ruochen Li, Kun Yuan, Yufei Xia +5

Surgical planning integrates visual perception, long-horizon reasoning, and procedural knowledge, yet it remains unclear whether current evaluation protocols reliably assess vision…

cs.CL2025

ReEvalMed: Rethinking Medical Report Evaluation by Aligning Metrics with Real-World Clinical Judgment

Ruochen Li, Jun Li, Bailiang Jian +2

Automatically generated radiology reports often receive high scores from existing evaluation metrics but fail to earn clinicians' trust. This gap reveals fundamental flaws in how c…

cs.CL2025★ 1 cited

Focus Directions Make Your Language Models Pay More Attention to Relevant Contexts

Youxiang Zhu, Ruochen Li, Danqing Wang +2

Long-context large language models (LLMs) are prone to be distracted by irrelevant contexts. The reason for distraction remains poorly understood. In this paper, we first identify…

eess.IV2024

Classification, Regression and Segmentation directly from k-Space in Cardiac MRI

Ruochen Li, Jiazhen Pan, Youxiang Zhu +2

Cardiac Magnetic Resonance Imaging (CMR) is the gold standard for diagnosing cardiovascular diseases. Clinical diagnoses predominantly rely on magnitude-only Digital Imaging and Co…