@inproceedings{lee-etal-2022-focus,
title = "Focus on {F}o{C}us: Is {F}o{C}us focused on Context, Knowledge and Persona?",
author = "Lee, SeungYoon and
Lee, Jungseob and
Park, Chanjun and
Eo, Sugyeong and
Moon, Hyeonseok and
Seo, Jaehyung and
Park, Jeongbae and
Lim, Heuiseok",
editor = "Lim, Heuiseok and
Kim, Seungryong and
Lee, Yeonsoo and
Lin, Steve and
Seo, Paul Hongsuck and
Suh, Yumin and
Jang, Yoonna and
Lim, Jungwoo and
Hur, Yuna and
Son, Suhyune",
booktitle = "Proceedings of the 1st Workshop on Customized Chat Grounding Persona and Knowledge",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.ccgpk-1.1",
pages = "1--8",
abstract = "Rather than continuing the conversation based on personalized or implicit information, the existing conversation system generates dialogue by focusing only on the superficial content. To solve this problem, FoCus was recently released. FoCus is a persona-knowledge grounded dialogue generation dataset that leverages Wikipedia{'}s knowledge and personal persona, focusing on the landmarks provided by Google, enabling user-centered conversation. However, a closer empirical study is needed since research in the field is still in its early stages. Therefore, we fling two research questions about FoCus. {``}Is the FoCus whether for conversation or question answering?{''} to identify the structural problems of the dataset. {``}Does the FoCus model do real knowledge blending?{''} to closely demonstrate that the model acquires actual knowledge. As a result of the experiment, we present that the FoCus model could not correctly blend the knowledge according to the input dialogue and that the dataset design is unsuitable for the multi-turn conversation.",
}
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<abstract>Rather than continuing the conversation based on personalized or implicit information, the existing conversation system generates dialogue by focusing only on the superficial content. To solve this problem, FoCus was recently released. FoCus is a persona-knowledge grounded dialogue generation dataset that leverages Wikipedia’s knowledge and personal persona, focusing on the landmarks provided by Google, enabling user-centered conversation. However, a closer empirical study is needed since research in the field is still in its early stages. Therefore, we fling two research questions about FoCus. “Is the FoCus whether for conversation or question answering?” to identify the structural problems of the dataset. “Does the FoCus model do real knowledge blending?” to closely demonstrate that the model acquires actual knowledge. As a result of the experiment, we present that the FoCus model could not correctly blend the knowledge according to the input dialogue and that the dataset design is unsuitable for the multi-turn conversation.</abstract>
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%0 Conference Proceedings
%T Focus on FoCus: Is FoCus focused on Context, Knowledge and Persona?
%A Lee, SeungYoon
%A Lee, Jungseob
%A Park, Chanjun
%A Eo, Sugyeong
%A Moon, Hyeonseok
%A Seo, Jaehyung
%A Park, Jeongbae
%A Lim, Heuiseok
%Y Lim, Heuiseok
%Y Kim, Seungryong
%Y Lee, Yeonsoo
%Y Lin, Steve
%Y Seo, Paul Hongsuck
%Y Suh, Yumin
%Y Jang, Yoonna
%Y Lim, Jungwoo
%Y Hur, Yuna
%Y Son, Suhyune
%S Proceedings of the 1st Workshop on Customized Chat Grounding Persona and Knowledge
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F lee-etal-2022-focus
%X Rather than continuing the conversation based on personalized or implicit information, the existing conversation system generates dialogue by focusing only on the superficial content. To solve this problem, FoCus was recently released. FoCus is a persona-knowledge grounded dialogue generation dataset that leverages Wikipedia’s knowledge and personal persona, focusing on the landmarks provided by Google, enabling user-centered conversation. However, a closer empirical study is needed since research in the field is still in its early stages. Therefore, we fling two research questions about FoCus. “Is the FoCus whether for conversation or question answering?” to identify the structural problems of the dataset. “Does the FoCus model do real knowledge blending?” to closely demonstrate that the model acquires actual knowledge. As a result of the experiment, we present that the FoCus model could not correctly blend the knowledge according to the input dialogue and that the dataset design is unsuitable for the multi-turn conversation.
%U https://aclanthology.org/2022.ccgpk-1.1
%P 1-8
Markdown (Informal)
[Focus on FoCus: Is FoCus focused on Context, Knowledge and Persona?](https://aclanthology.org/2022.ccgpk-1.1) (Lee et al., CCGPK 2022)
ACL
- SeungYoon Lee, Jungseob Lee, Chanjun Park, Sugyeong Eo, Hyeonseok Moon, Jaehyung Seo, Jeongbae Park, and Heuiseok Lim. 2022. Focus on FoCus: Is FoCus focused on Context, Knowledge and Persona?. In Proceedings of the 1st Workshop on Customized Chat Grounding Persona and Knowledge, pages 1–8, Gyeongju, Republic of Korea. Association for Computational Linguistics.