ECLAIR: Enhanced Clarification for Interactive Responses

John Murzaku, Zifan Liu, Md Mehrab Tanjim, Vaishnavi Muppala, Xiang Chen +1 more
3/19/2025
cs.AI

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Abstract

We present ECLAIR (Enhanced CLArification for Interactive Responses), a novel unified and end-to-end framework for interactive disambiguation in enterprise AI assistants. ECLAIR generates clarification questions for ambiguous user queries and resolves ambiguity based on the user's response.We introduce a generalized architecture capable of integrating ambiguity information from multiple downstream agents, enhancing context-awareness in resolving ambiguities and allowing enterprise specific definition of agents. We further define agents within our system that provide domain-specific grounding information. We conduct experiments comparing ECLAIR to few-shot prompting techniques and demonstrate ECLAIR's superior performance in clarification question generation and ambiguity resolution.

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Cite this paper

@article{murzaku2025eclair,
  title  = {ECLAIR: Enhanced Clarification for Interactive Responses},
  author = {John Murzaku and Zifan Liu and Md Mehrab Tanjim and Vaishnavi Muppala and Xiang Chen and Yunyao Li},
  year   = {2025},
  eprint = {2503.15739},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.15739v1}
}

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