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A focused feed for RLHF, preference data, rater protocols, agent evaluation, and LLM-as-judge research. Every paper includes structured metadata for quick triage.

Total papers: 13 Search mode: keyword RSS

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SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video

Guanyi Qin, Xiaozhen Wang, Zhu Zhuo, Chang Han Low, Yuancan Xiao, Yibing Fu · Feb 25, 2026

Citations: 0
Expert Verification Automatic Metrics MedicineCoding
  • Existing AI systems offer binary safety verification or static detection, ignoring the phase-dependent nature of intraoperative reasoning.
  • We introduce ResGo, a benchmark of laparoscopic frames annotated with Go Zone bounding boxes and clinician-authored rationales covering phase, exposure quality reasoning, next action and risk reminder.
Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics

Yue Pan, Xingyao Wang, Hanyue Zhang, Liwei Liu, Changxin Li, Gang Yang · Feb 23, 2026

Citations: 0
Automatic Metrics Long Horizon MedicineCoding
  • The model's high sensitivity was further corroborated by additional follow-up data, confirming its efficacy in predicting HF deterioration and its potential to secure patient safety in remote, home-based settings.
MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models

Boqi Chen, Xudong Liu, Jiachuan Peng, Marianne Frey-Marti, Bang Zheng, Kyle Lam · Feb 25, 2026

Citations: 0
Expert Verification Automatic Metrics MedicineCoding
  • Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world clinical complexity.
  • We introduce MEDSYN, a multilingual, multimodal benchmark of highly complex clinical cases with up to 7 distinct visual clinical evidence (CE) types per case.
What Makes a Good Doctor Response? An Analysis on a Romanian Telemedicine Platform

Adrian Cosma, Cosmin Dumitrache, Emilian Radoi · Feb 19, 2026

Citations: 0
Expert Verification Automatic Metrics Medicine
  • As platforms increasingly rely on patient ratings and feedback, clinicians face growing pressure to maintain satisfaction scores, even though these evaluations often reflect communication quality more than clinical accuracy.
MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation

Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding · Mar 23, 2025

Citations: 0
Expert Verification Automatic Metrics Medicine
  • Comprehensive evaluation demonstrates that our method significantly outperforms baseline approaches in both assessment accuracy and treatment plan quality.
Confusion-Aware Rubric Optimization for LLM-based Automated Grading

Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Joseph Krajcik, Namsoo Shin · Feb 28, 2026

Citations: 0
Rubric Rating Automatic Metrics Medicine
  • Empirical evaluations on teacher education and STEM datasets demonstrate that CARO significantly outperforms existing SOTA methods.
From Medical Records to Diagnostic Dialogues: A Clinical-Grounded Approach and Dataset for Psychiatric Comorbidity

Tianxi Wan, Jiaming Luo, Siyuan Chen, Kunyao Lan, Jianhua Chen, Haiyang Geng · Oct 29, 2025

Citations: 0
Automatic Metrics Multi Agent Medicine
  • To address this, we develop a novel approach integrating synthetic patient electronic medical record (EMR) construction and multi-agent diagnostic dialogue generation.
  • Our multi-agent framework transfers the clinical interview protocol into a hierarchical state machine and context tree, supporting over 130 diagnostic states while maintaining clinical standards.
When Metrics Disagree: Automatic Similarity vs. LLM-as-a-Judge for Clinical Dialogue Evaluation

Bian Sun, Zhenjian Wang, Orvill de la Torre, Zirui Wang · Feb 27, 2026

Citations: 0
Llm As JudgeAutomatic Metrics Medicine
  • This paper details the baseline model selection, fine-tuning process, evaluation methods, and the implications of deploying more accurate LLMs in healthcare settings.
  • The fine-tuned model demonstrated significant improvements across all key dimensions except GPT-4's evaluation.
Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP

Lorenz Hufe, Constantin Venhoff, Erblina Purelku, Maximilian Dreyer, Sebastian Lapuschkin, Wojciech Samek · Aug 28, 2025

Citations: 0
Red Team Automatic Metrics MedicineCoding
  • These models serve as suitable drop-in replacements for a broad range of safety-critical applications, where the risks of text-based manipulation outweigh the utility of text recognition.
Citations: 0
Automatic Metrics Long Horizon MedicineCoding
  • With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction.
  • To address these challenges, we introduce AgenticRAGTracer, the first Agentic RAG benchmark that is primarily constructed automatically by large language models and designed to support step-by-step validation.
Moving Beyond Medical Exams: A Clinician-Annotated Fairness Dataset of Real-World Tasks and Ambiguity in Mental Healthcare

Max Lamparth, Declan Grabb, Amy Franks, Scott Gershan, Kaitlyn N. Kunstman, Aaron Lulla · Feb 22, 2025

Citations: 0
Pairwise PreferenceExpert Verification Automatic Metrics Medicine
  • Current medical language model (LM) benchmarks often over-simplify the complexities of day-to-day clinical practice tasks and instead rely on evaluating LMs on multiple-choice board exam questions.
  • We outline a series of intended use cases and demonstrate the usability of our dataset by evaluating sixteen off-the-shelf and six (mental) health fine-tuned LMs on category-specific task accuracy, on the fairness impact of patient…
A Scalable Framework for Evaluating Health Language Models

Neil Mallinar, A. Ali Heydari, Xin Liu, Anthony Z. Faranesh, Brent Winslow, Nova Hammerquist · Mar 30, 2025

Citations: 0
Rubric RatingExpert Verification Automatic Metrics Medicine
  • As LLM-driven health applications are increasingly adopted, rigorous and efficient one-sided evaluation methodologies are crucial to ensure response quality across multiple dimensions, including accuracy, personalization and safety.
  • In this work, we introduce Adaptive Precise Boolean rubrics: an evaluation framework that streamlines human and automated evaluation of open-ended questions by identifying gaps in model responses using a minimal set of targeted rubrics…
A Multi-Agent Framework for Medical AI: Leveraging Fine-Tuned GPT, LLaMA, and DeepSeek R1 for Evidence-Based and Bias-Aware Clinical Query Processing

Naeimeh Nourmohammadi, Md Meem Hossain, The Anh Han, Safina Showkat Ara, Zia Ush Shamszaman · Feb 15, 2026

Citations: 0
Automatic Metrics Multi Agent Medicine
  • We propose a multi-agent medical QA framework that combines complementary LLMs with evidence retrieval, uncertainty estimation, and bias checks to improve answer reliability.
  • DeepSeek R1 achieves the strongest scores (ROUGE-1 0.536 +- 0.04; ROUGE-2 0.226 +-0.03; BLEU 0.098 -+ 0.018) and substantially outperforms the specialised biomedical baseline BioGPT in zero-shot evaluation.

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