Task-Oriented Conversational Modeling with Subjective Knowledge Track in DSTC11

Seokhwan Kim, Spandana Gella, Chao Zhao, Di Jin, Alexandros Papangelis, Behnam Hedayatnia, Yang Liu, Dilek Z Hakkani-Tur


Abstract
Conventional Task-oriented Dialogue (TOD) Systems rely on domain-specific APIs/DBs or external factual knowledge to create responses. In DSTC11 track 5, we aims to provide a new challenging task to accommodate subjective user requests (e.g.,”Is the WIFI reliable?” or “Does the restaurant have a good atmosphere?” into TOD. We release a benchmark dataset, which contains subjective knowledge-seeking dialogue contexts and manually annotated responses that are grounded in subjective knowledge sources. The challenge track received a total of 48 entries from 14 participating teams.
Anthology ID:
2023.dstc-1.29
Volume:
Proceedings of The Eleventh Dialog System Technology Challenge
Month:
September
Year:
2023
Address:
Prague, Czech Republic
Editors:
Yun-Nung Chen, Paul Crook, Michel Galley, Sarik Ghazarian, Chulaka Gunasekara, Raghav Gupta, Behnam Hedayatnia, Satwik Kottur, Seungwhan Moon, Chen Zhang
Venues:
DSTC | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
274–281
Language:
URL:
https://aclanthology.org/2023.dstc-1.29
DOI:
Bibkey:
Cite (ACL):
Seokhwan Kim, Spandana Gella, Chao Zhao, Di Jin, Alexandros Papangelis, Behnam Hedayatnia, Yang Liu, and Dilek Z Hakkani-Tur. 2023. Task-Oriented Conversational Modeling with Subjective Knowledge Track in DSTC11. In Proceedings of The Eleventh Dialog System Technology Challenge, pages 274–281, Prague, Czech Republic. Association for Computational Linguistics.
Cite (Informal):
Task-Oriented Conversational Modeling with Subjective Knowledge Track in DSTC11 (Kim et al., DSTC-WS 2023)
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PDF:
https://aclanthology.org/2023.dstc-1.29.pdf