@inproceedings{kim-etal-2023-concept,
title = "Concept-based Persona Expansion for Improving Diversity of Persona-Grounded Dialogue",
author = "Kim, Donghyun and
Ahn, Youbin and
Lee, Chanhee and
Kim, Wongyu and
Lee, Kyong-Ho and
Shin, Donghoon and
Lee, Yeonsoo",
editor = "Vlachos, Andreas and
Augenstein, Isabelle",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.252",
doi = "10.18653/v1/2023.eacl-main.252",
pages = "3471--3481",
abstract = "A persona-grounded dialogue model aims to improve the quality of responses to promote user engagement. However, because the given personas are mostly short and limited to only a few informative words, it is challenging to utilize them to generate diverse responses. To tackle this problem, we propose a novel persona expansion framework, Concept-based Persona eXpansion (CPX). CPX takes the original persona as input and generates expanded personas that contain conceptually rich content. We constitute CPX with two task modules: 1) Concept Extractor and 2) Sentence Generator. To train these modules, we exploit the duality of two tasks with a commonsense dataset consisting of a concept set and the corresponding sentences which contain the given concepts. Extensive experiments on persona expansion and response generation show that our work sufficiently contributes to improving the quality of responses in diversity and richness.",
}
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<abstract>A persona-grounded dialogue model aims to improve the quality of responses to promote user engagement. However, because the given personas are mostly short and limited to only a few informative words, it is challenging to utilize them to generate diverse responses. To tackle this problem, we propose a novel persona expansion framework, Concept-based Persona eXpansion (CPX). CPX takes the original persona as input and generates expanded personas that contain conceptually rich content. We constitute CPX with two task modules: 1) Concept Extractor and 2) Sentence Generator. To train these modules, we exploit the duality of two tasks with a commonsense dataset consisting of a concept set and the corresponding sentences which contain the given concepts. Extensive experiments on persona expansion and response generation show that our work sufficiently contributes to improving the quality of responses in diversity and richness.</abstract>
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%0 Conference Proceedings
%T Concept-based Persona Expansion for Improving Diversity of Persona-Grounded Dialogue
%A Kim, Donghyun
%A Ahn, Youbin
%A Lee, Chanhee
%A Kim, Wongyu
%A Lee, Kyong-Ho
%A Shin, Donghoon
%A Lee, Yeonsoo
%Y Vlachos, Andreas
%Y Augenstein, Isabelle
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F kim-etal-2023-concept
%X A persona-grounded dialogue model aims to improve the quality of responses to promote user engagement. However, because the given personas are mostly short and limited to only a few informative words, it is challenging to utilize them to generate diverse responses. To tackle this problem, we propose a novel persona expansion framework, Concept-based Persona eXpansion (CPX). CPX takes the original persona as input and generates expanded personas that contain conceptually rich content. We constitute CPX with two task modules: 1) Concept Extractor and 2) Sentence Generator. To train these modules, we exploit the duality of two tasks with a commonsense dataset consisting of a concept set and the corresponding sentences which contain the given concepts. Extensive experiments on persona expansion and response generation show that our work sufficiently contributes to improving the quality of responses in diversity and richness.
%R 10.18653/v1/2023.eacl-main.252
%U https://aclanthology.org/2023.eacl-main.252
%U https://doi.org/10.18653/v1/2023.eacl-main.252
%P 3471-3481
Markdown (Informal)
[Concept-based Persona Expansion for Improving Diversity of Persona-Grounded Dialogue](https://aclanthology.org/2023.eacl-main.252) (Kim et al., EACL 2023)
ACL