@inproceedings{62a5db67111c424f8f95e7dda1db7197,
title = "SLDT: Sequential Latent Document Transformer for Multilingual Document-based Dialogue",
abstract = "Multilingual document-grounded dialogue, where the system is required to generate responses based on both the conversation multilingual context and external knowledge sources. Traditional pipeline methods for knowledge identification and response generation, while effective in certain scenarios, suffer from error propagation issues and fail to capture the interdependence between these two sub-tasks. To overcome these challenges, we propose the application of the SLDT method, which treats passage-knowledge selection as a sequential decision process rather than a single-step decision process. We achieved the winner 3rd in dialdoc 2023 and we also validated the effectiveness of our method on other datasets. The ablation experiment also shows that our method significantly improves the basic model compared to other methods.",
author = "Zhanyu Ma and Zeming Liu and Jian Ye",
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 = "57--67",
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",
}