Retrieval-Augmented Agentic Rubric Generation for Reliable Medical Response Evaluation

arXiv:2601.15161 · cs.CL, cs.AI · Submitted 2026-01-21 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-01-21

Updated: 2026-08-26

Code: https://github.com/AmbeChen/Automated-Rubric-Generation

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 15× in this paper · explained in 1 episode
• Alignment — 13× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Clinical Intent Alignment — 9× in this paper
• Hallucination — 9× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 8× in this paper · explained in 3 episodes
• Multi-Agent Framework — 8× in this paper · explained in 3 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Grounding — 6× in this paper · explained in 3 episodes
• LLM judge — 4× in this paper · explained in 2 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Iterative Refinement — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Evaluation Dimensions — 1× in this paper · explained in 3 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes

Sources

• HealthBench: Evaluating Large Language Models Towards Improved Human Health
• On the Opportunities and Risks of Foundation Models
• Superhuman performance of a large language model on the reasoning tasks of a physician
• Medical Hallucinations in Foundation Models and Their Impact on Healthcare
• An Empirical Study of LLM-as-a-Judge: How Design Choices Impact Evaluation Reliability
• LLMEval-Med: A Real-world Clinical Benchmark for Medical LLMs with Physician Validation
• A Survey of Large Language Models

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering