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arXiv · 2204.03930

From Rewriting to Remembering: Common Ground for Conversational QA Models

Marco Del Tredici·Xiaoyu Shen·Gianni Barlacchi·Bill Byrne·Adrià de Gispert
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Abstract

In conversational QA, models have to leverage information in previous turns to answer upcoming questions. Current approaches, such as Question Rewriting, struggle to extract relevant information as the conversation unwinds. We introduce the Common Ground (CG), an approach to accumulate conversational information as it emerges and select the relevant information at every turn. We show that CG offers a more efficient and human-like way to exploit conversational information compared to existing approaches, leading to improvements on Open Domain Conversational QA.

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Marco Del Tredici, Xiaoyu Shen, Gianni Barlacchi, Bill Byrne, Adrià de Gispert. 2022-04-08. From Rewriting to Remembering: Common Ground for Conversational QA Models. https://arxiv.org/abs/2204.03930

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