Exploration of multilingual prompts in document-grounded dialogue

Xiaocheng Zhang, Huang Qing, Fu Lin


Abstract
Transferring DGD models from high-resource languages to low-resource languages is a meaningful but challenging task. Being able to provide multilingual responses to multilingual documents further complicates the task. This paper describes our method at DialDoc23 Shared Task (Document-Grounded Dialogue and Conversational Question Answering) for generate responses based on the most relevant passage retrieved. We divide it into three steps of retrieval, re-ranking and generation. Our methods include negative sample augmentation, prompt learning, pseudo-labeling and ensemble. On the submission page, we rank 2nd based on the sum of token-level F1, SacreBleu and Rouge-L scores used for the final evaluation, and get the total score of 210.25.
Anthology ID:
2023.dialdoc-1.3
Volume:
Proceedings of the Third DialDoc Workshop on Document-grounded Dialogue and Conversational Question Answering
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Smaranda Muresan, Vivian Chen, Kennington Casey, Vandyke David, Dethlefs Nina, Inoue Koji, Ekstedt Erik, Ultes Stefan
Venue:
dialdoc
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
30–35
Language:
URL:
https://aclanthology.org/2023.dialdoc-1.3
DOI:
10.18653/v1/2023.dialdoc-1.3
Bibkey:
Cite (ACL):
Xiaocheng Zhang, Huang Qing, and Fu Lin. 2023. Exploration of multilingual prompts in document-grounded dialogue. In Proceedings of the Third DialDoc Workshop on Document-grounded Dialogue and Conversational Question Answering, pages 30–35, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Exploration of multilingual prompts in document-grounded dialogue (Zhang et al., dialdoc 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.dialdoc-1.3.pdf