Quantifying and Mitigating Premature Closure in Frontier LLMs
arXiv:2605.15000v1 Announce Type: cross
Abstract: Premature closure, or committing to a conclusion before sufficient information is available, is a recognized contributor to diagnostic error but remains underexamined in large language models (LLMs). W…