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Diverse Multi-Answer Retrieval with Determinantal Point Processes (2211.16029v1)

Published 29 Nov 2022 in cs.CL and cs.IR

Abstract: Often questions provided to open-domain question answering systems are ambiguous. Traditional QA systems that provide a single answer are incapable of answering ambiguous questions since the question may be interpreted in several ways and may have multiple distinct answers. In this paper, we address multi-answer retrieval which entails retrieving passages that can capture majority of the diverse answers to the question. We propose a re-ranking based approach using Determinantal point processes utilizing BERT as kernels. Our method jointly considers query-passage relevance and passage-passage correlation to retrieve passages that are both query-relevant and diverse. Results demonstrate that our re-ranking technique outperforms state-of-the-art method on the AmbigQA dataset.

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Authors (3)
  1. Poojitha Nandigam (2 papers)
  2. Nikhil Rayaprolu (1 paper)
  3. Manish Shrivastava (62 papers)
Citations (1)

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