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Human Feedback and Eval Paper Explorer

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Total papers: 6 Search mode: keyword Shortlist (0) RSS

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Self-Preference Bias in Rubric-Based Evaluation of Large Language Models

José Pombal, Ricardo Rei, André F. T. Martins · Apr 8, 2026

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 90% Moderate protocol signal Freshness: Hot Status: Ready
Pairwise PreferenceRubric Rating Llm As Judge Medicine
  • We present the first study of SPB in rubric-based evaluation, an increasingly popular benchmarking paradigm where judges issue binary verdicts on individual evaluation criteria, instead of assigning holistic scores or rankings.
  • Using IFEval, a benchmark with programmatically verifiable rubrics, we show that SPB persists even when evaluation criteria are entirely objective: among rubrics where generators fail, judges can be up to 50\% more likely to incorrectly…
Open paper
DeCode: Decoupling Content and Delivery for Medical QA

Po-Jen Ko, Chen-Han Tsai, Yu-Shao Peng · Jan 5, 2026

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 83% Moderate protocol signal Freshness: Warm Status: Ready
Automatic Metrics Medicine
  • We evaluate DeCode on OpenAI HealthBench, a comprehensive and challenging benchmark designed to assess clinical relevance and validity of LLM responses.
Open paper
PanCanBench: A Comprehensive Benchmark for Evaluating Large Language Models in Pancreatic Oncology

Yimin Zhao, Sheela R. Damle, Simone E. Dekker, Scott Geng, Karly Williams Silva, Jesse J Hubbard · Mar 2, 2026

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 83% High protocol signal Freshness: Warm Status: Fallback
Rubric RatingExpert Verification Llm As JudgeAutomatic Metrics Medicine
  • Large language models (LLMs) have achieved expert-level performance on standardized examinations, yet multiple-choice accuracy poorly reflects real-world clinical utility and safety.
  • We evaluated 22 proprietary and open-source LLMs using an LLM-as-a-judge framework, measuring clinical completeness, factual accuracy, and web-search integration.
Open paper
Decomposing Physician Disagreement in HealthBench

Satya Borgohain, Roy Mariathas · Feb 26, 2026

Citations: 0

Match reason: Title directly matches "Healthbench".

Score: 80% Moderate protocol signal Freshness: Warm Status: Fallback
Rubric Rating Medicine
  • We decompose physician disagreement in the HealthBench medical AI evaluation dataset to understand where variance resides and what observable features can explain it.
  • The agreement ceiling in medical AI evaluation is thus largely structural, but the reducible/irreducible dissociation suggests that closing information gaps in evaluation scenarios could lower disagreement where inherent clinical ambiguity…
Open paper
Healthy LLMs? Benchmarking LLM Knowledge of UK Government Public Health Information

Joshua Harris, Fan Grayson, Felix Feldman, Timothy Laurence, Toby Nonnenmacher, Oliver Higgins · May 9, 2025

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 78% High protocol signal Freshness: Cold Status: Fallback
Automatic Metrics Web Browsing Medicine
  • However, while there are a number of LLM benchmarks in the medical domain, currently little is known about LLM knowledge within the field of public health.
  • Assessing 24 LLMs on PubHealthBench we find the latest proprietary LLMs (GPT-4.5, GPT-4.1 and o1) have a high degree of knowledge, achieving >90% accuracy in the MCQA setup, and outperform humans with cursory search engine use.
Open paper

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