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Paper · arXiv

Clarification Is Not Correction: LLMs Fail to Let Go

Dialogue failures in language models are usually framed as memory failures: context too long, summaries lossy, a constraint forgotten. We argue this misses a deeper problem: in many conversations the model does not forget, it commits too early. An ambiguous early turn collapses into a single hidden interpretation, and later clarification is filtered through that commitment. We call this early posterior collapse: unresolved user intent collapsing into a committed task state before ambiguity is resolved. We study it with controlled dialogue tasks in writing, planning, and coding using Gemini-2.5-Pro and Gemini-2.5-Flash. Across thousands of trials, the same information in different orders y...

AuthorsJianzhe Lin, Xiaolin Li, Fei Wang et al.
Primary categorycs.AI
Published21 September 2026
Last updated at source21 September 2026
cs.AI
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