DialDoc 2021 Shared Task: Goal-Oriented Document-grounded Dialogue Modeling

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Abstract

We present the results of Shared Task at Workshop DialDoc 2021 that is focused on document-grounded dialogue and conversational question answering. The primary goal of this Shared Task is to build goal-oriented information-seeking conversation systems that can identify the most relevant knowledge in the associated document for generating agent responses in natural language. It includes two subtasks on predicting agent responses: the first subtask is to predict the grounding text span in the given document for next agent response; the second subtask is to generate agent response in natural language given the context. Many submissions outperform baseline significantly. For the first task, the best-performing system achieved 67.1 Exact Match and 76.3 F1. For the second subtask, the best system achieved 41.1 SacreBLEU and highest rank by human evaluation.

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APA

Feng, S. (2021). DialDoc 2021 Shared Task: Goal-Oriented Document-grounded Dialogue Modeling. In DialDoc 2021 - 1st Workshop on Document-Grounded Dialogue and Conversational Question Answering, Proceedings (pp. 1–7). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.dialdoc-1.1

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