gankim/tree-of-clarifications
π² Code for our EMNLP 2023 paper - π "Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models"
This helps researchers, knowledge managers, or content creators generate comprehensive, long-form answers to complex and ambiguous questions. It takes an ambiguous question and optionally external search results, then uses an advanced AI to explore different interpretations. The output is a detailed answer that addresses the nuances of the original question, making it useful for deep inquiry and content generation.
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Use this if you need to provide thorough, multi-faceted answers to questions that can be interpreted in several ways, and you want to ensure all reasonable angles are covered.
Not ideal if you need quick, single-fact answers or if your questions are always straightforward and unambiguous.
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Python
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Last pushed
Dec 04, 2023
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