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SUP-MIMIC: A Multi-Task Clinical Diagnosis Benchmark for Evaluating LLMs' Robustness to Contradictory Evidence

Paper recorded by Signals 4 on 2026-08-30 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.AI · 人工智能 · first seen 2026-09-01

Abstract

Current evaluations of large language models (LLMs) primarily focus on factual knowledge retrieval, overlooking the fundamental challenge of navigating the complex, non-bijective mappings between clinical indicators and diagnoses. Existing benchmarks fail to assess whether large language models truly possess the reasoning capability required for diagnostic ambiguity scenarios, where identical clin

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#274 most recent of 300 cs.AI papers we have recorded · ↑ newer: Call Neighbours Yourself: Graph Walks with Destination-Conditioned On- · ↓ older: HoopMind: A Real-Time Neural Game-Tree System for Opponent-Aware Posse
Cite this page: SUP-MIMIC: A Multi-Task Clinical Diagnosis Benchmark for Evaluating LLMs' Robustness to Contradictory Evidence: the #274 most recent of 300 cs.AI papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/sup-mimic-a-multi-task-clinical-diagnosis-benchmark-for-evaluating-llms-robustne.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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