ECLAIR: Enhanced Clarification for Interactive Responses

Authors

  • John Murzaku State University of New York at Stony Brook
  • Zifan Liu Adobe
  • Md Mehrab Tanjim Adobe Research
  • Vaishnavi Muppala Adobe
  • Xiang Chen Adobe Research
  • Yunyao Li Adobe

DOI:

https://doi.org/10.1609/aaai.v39i28.35152

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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Published

2025-04-11

How to Cite

Murzaku, J., Liu, Z., Tanjim, M. M., Muppala, V., Chen, X., & Li, Y. (2025). ECLAIR: Enhanced Clarification for Interactive Responses. Proceedings of the AAAI Conference on Artificial Intelligence, 39(28), 28864–28870. https://doi.org/10.1609/aaai.v39i28.35152