arXiv — NLP / Computation & Language · · 3 min read

Clarification Is Not Enough: Post-Clarification Answering Remains the Bottleneck in Multi-Turn QA

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Computer Science > Computation and Language

arXiv:2605.25204 (cs)
[Submitted on 24 May 2026]

Title:Clarification Is Not Enough: Post-Clarification Answering Remains the Bottleneck in Multi-Turn QA

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Abstract:Pluralistic alignment requires systems to adapt to diverse user values, communication styles, and contextual assumptions. We believe that a foundational prerequisite for such alignment enabling accurate preference elicitation from people when their intent is under-specified or ambiguous. We study the problem of preference elicitation in multi-turn question answering by decomposing the problem into two components: a \textbf{clarification policy}, which decides whether to ask a clarifying question or answer directly, and \textbf{post-clarification answering}, which produces the correct final answer once the missing information is provided. We show, using the PACIFIC benchmark, that supervised fine-tuning rapidly improves the clarification policy, however, final answer accuracy remains substantially lower even when the model takes the correct action. This gap indicates that understanding and correctly interpreting the user's response is the critical gap in multi-turn question-answering systems.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2605.25204 [cs.CL]
  (or arXiv:2605.25204v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.25204
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Jinyan Su [view email]
[v1] Sun, 24 May 2026 18:06:09 UTC (742 KB)
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