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papersTODAY 04:00 UTC

Study examines hindsight bias in clinical LLM temporal reasoning

A new arXiv paper argues that clinical language models are frequently assessed on retrospective patient records that already contain the eventual diagnosis, treatment response and outcome. Because those records expose information a real prospective decision-maker would not have, such benchmarks may reward models for exploiting future data instead of genuine reasoning. The work examines how this exposure shapes model judgments in clinical temporal tasks.

arXiv benchmark-contamination clinical-llm-evaluation hindsight-bias retrospective-patient-records temporal reasoning

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.AIHindsight Bias in Clinical Temporal Reasoning: How Future Data Exposure Affects Large Language Model Judgment ↗TODAY 04:00 UTC

arXiv cs.CLHindsight Bias in Clinical Temporal Reasoning: How Future Data Exposure Affects Large Language Model Judgment ↗TODAY 04:00 UTC