@inproceedings{8cf1d3c76a61499b8c23c11729d2dffa,
title = "Exploration of multilingual prompts in document-grounded dialogue",
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.",
author = "Xiaocheng Zhang and Xuelin Fu and Yongqing Huang and Xiaohong Su",
note = "Publisher Copyright: {\textcopyright} 2023 Association for Computational Linguistics.; 3rd Workshop on Document-grounded Dialogue and Conversational Question Answering, DialDoc 2023, co-located with ACL 2023 ; Conference date: 13-07-2023",
year = "2023",
language = "英语",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "30--35",
editor = "Smaranda Muresan and Vivian Chen and Casey Kennington and David Vandyke and Nina Dethlefs and Koji Inoue and Erik Ekstedt and Stefan Ultes",
booktitle = "DialDoc 2023 - Proceedings of the 3rd DialDoc Workshop on Document-Grounded Dialogue and Conversational Question Answering, Proceedings of the Workshop",
address = "澳大利亚",
}