@inproceedings{0982255385374a1c9977a2c6ec0e5e98,
title = "KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation",
abstract = "Existing knowledge-grounded conversation systems generate responses typically in a retrieve-then-generate manner. They require a large knowledge base and a strong knowledge retrieval component, which is time- and resource-consuming. In this paper, we address the challenge by leveraging the inherent knowledge encoded in the pre-trained language models (PLMs). We propose Knowledgeable Prefix Tuning (KnowPrefix-Tuning), a two-stage tuning framework, bypassing the retrieval process in a knowledge-grounded conversation system by injecting prior knowledge into the lightweight knowledge prefix. The knowledge prefix is a sequence of continuous knowledge-specific vectors that can be learned during training. In addition, we propose a novel interactive re-parameterization mechanism that allows the prefix to interact fully with the PLM during the optimization of response generation. Experimental results demonstrate that KnowPrefix-Tuning outperforms fine-tuning and other lightweight tuning approaches, and performs comparably with strong retrieval-based baselines while being faster during inference (The code is available at https://github.com/fantast4ever/KnowPrefix-Tuning.)",
keywords = "Dialogue generation, Knowledge-grounded dialogue, Parameter-efficient fine-tuning, Pre-trained language models",
author = "Jiaqi Bai and Zhao Yan and Ze Yang and Jian Yang and Xinnian Liang and Hongcheng Guo and Zhoujun Li",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 23rd Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023 ; Conference date: 18-09-2023 Through 22-09-2023",
year = "2023",
doi = "10.1007/978-3-031-43415-0\_31",
language = "英语",
isbn = "9783031434143",
series = "Lecture Notes in Computer Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "525--542",
editor = "Danai Koutra and Claudia Plant and \{Gomez Rodriguez\}, Manuel and Elena Baralis and Francesco Bonchi",
booktitle = "Machine Learning and Knowledge Discovery in Databases",
address = "德国",
}