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

Song Feng


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.
Anthology ID:
2021.dialdoc-1.1
Volume:
Proceedings of the 1st Workshop on Document-grounded Dialogue and Conversational Question Answering (DialDoc 2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | dialdoc
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–7
Language:
URL:
https://aclanthology.org/2021.dialdoc-1.1
DOI:
10.18653/v1/2021.dialdoc-1.1
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.dialdoc-1.1.pdf