“None of the Above”: Measure Uncertainty in Dialog Response Retrieval

Yulan Feng, Shikib Mehri, Maxine Eskenazi, Tiancheng Zhao


Abstract
This paper discusses the importance of uncovering uncertainty in end-to-end dialog tasks and presents our experimental results on uncertainty classification on the processed Ubuntu Dialog Corpus. We show that instead of retraining models for this specific purpose, we can capture the original retrieval model’s underlying confidence concerning the best prediction using trivial additional computation.
Anthology ID:
2020.acl-main.182
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2013–2020
Language:
URL:
https://aclanthology.org/2020.acl-main.182
DOI:
10.18653/v1/2020.acl-main.182
Bibkey:
Cite (ACL):
Yulan Feng, Shikib Mehri, Maxine Eskenazi, and Tiancheng Zhao. 2020. “None of the Above”: Measure Uncertainty in Dialog Response Retrieval. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2013–2020, Online. Association for Computational Linguistics.
Cite (Informal):
“None of the Above”: Measure Uncertainty in Dialog Response Retrieval (Feng et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.182.pdf
Video:
 http://slideslive.com/38929205