Possible or Definite? A Benchmark for Evaluating Diagnostic Uncertainty Preservation in Clinical Text

arXiv:2606.18471v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for clinical text tasks such as summarization and revision. While most studies evaluate the fluency and coherence of LLM-generated text, whether LLMs correctly preserve diagnostic uncertainty remains underexplored. In clinical practice, phrases such as ``possible pneumonia'' communicate the strength of available evidence and directly guide decisions about follow-up testing and treatment. Altering these uncertainty expressions can change the clinical meaning entirely. In this paper, we systematica

Source: arXiv cs.CL — read the full report at the original publisher.

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