@inproceedings{kim-etal-2023-task,
title = "Task-Oriented Conversational Modeling with Subjective Knowledge Track in {DSTC}11",
author = "Kim, Seokhwan and
Gella, Spandana and
Zhao, Chao and
Jin, Di and
Papangelis, Alexandros and
Hedayatnia, Behnam and
Liu, Yang and
Z Hakkani-Tur, Dilek",
editor = "Chen, Yun-Nung and
Crook, Paul and
Galley, Michel and
Ghazarian, Sarik and
Gunasekara, Chulaka and
Gupta, Raghav and
Hedayatnia, Behnam and
Kottur, Satwik and
Moon, Seungwhan and
Zhang, Chen",
booktitle = "Proceedings of The Eleventh Dialog System Technology Challenge",
month = sep,
year = "2023",
address = "Prague, Czech Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.dstc-1.29",
pages = "274--281",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Task-Oriented Conversational Modeling with Subjective Knowledge Track in DSTC11
%A Kim, Seokhwan
%A Gella, Spandana
%A Zhao, Chao
%A Jin, Di
%A Papangelis, Alexandros
%A Hedayatnia, Behnam
%A Liu, Yang
%A Z Hakkani-Tur, Dilek
%Y Chen, Yun-Nung
%Y Crook, Paul
%Y Galley, Michel
%Y Ghazarian, Sarik
%Y Gunasekara, Chulaka
%Y Gupta, Raghav
%Y Hedayatnia, Behnam
%Y Kottur, Satwik
%Y Moon, Seungwhan
%Y Zhang, Chen
%S Proceedings of The Eleventh Dialog System Technology Challenge
%D 2023
%8 September
%I Association for Computational Linguistics
%C Prague, Czech Republic
%F kim-etal-2023-task
%X 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.
%U https://aclanthology.org/2023.dstc-1.29
%P 274-281
Markdown (Informal)
[Task-Oriented Conversational Modeling with Subjective Knowledge Track in DSTC11](https://aclanthology.org/2023.dstc-1.29) (Kim et al., DSTC-WS 2023)
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.