@inproceedings{baez-santamaria-etal-2022-evaluating,
title = "Evaluating Agent Interactions Through Episodic Knowledge Graphs",
author = "Baez Santamaria, Selene and
Vossen, Piek and
Baier, Thomas",
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-1.3",
pages = "15--28",
abstract = "We present a new method based on episodic Knowledge Graphs (eKGs) for evaluating (multimodal) conversational agents in open domains. This graph is generated by interpreting raw signals during conversation and is able to capture the accumulation of knowledge over time. We apply structural and semantic analysis of the resulting graphs and translate the properties into qualitative measures. We compare these measures with existing automatic and manual evaluation metrics commonly used for conversational agents. Our results show that our Knowledge-Graph-based evaluation provides more qualitative insights into interaction and the agent{'}s behavior.",
}
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%0 Conference Proceedings
%T Evaluating Agent Interactions Through Episodic Knowledge Graphs
%A Baez Santamaria, Selene
%A Vossen, Piek
%A Baier, Thomas
%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 baez-santamaria-etal-2022-evaluating
%X We present a new method based on episodic Knowledge Graphs (eKGs) for evaluating (multimodal) conversational agents in open domains. This graph is generated by interpreting raw signals during conversation and is able to capture the accumulation of knowledge over time. We apply structural and semantic analysis of the resulting graphs and translate the properties into qualitative measures. We compare these measures with existing automatic and manual evaluation metrics commonly used for conversational agents. Our results show that our Knowledge-Graph-based evaluation provides more qualitative insights into interaction and the agent’s behavior.
%U https://aclanthology.org/2022.ccgpk-1.3
%P 15-28
Markdown (Informal)
[Evaluating Agent Interactions Through Episodic Knowledge Graphs](https://aclanthology.org/2022.ccgpk-1.3) (Baez Santamaria et al., CCGPK 2022)
ACL