@inproceedings{c0b81607f60b4fd3af72080a5d2afd09,
title = "Dialogue Response Evaluation Model with Conversational Feature Sensitive Negative Sampling",
abstract = "Evaluating the conversational responses is a challenging task. This is because there are so many possible responses in open-domain conversation. Recent work finds that appropriate negative samples are effective in practice, but there was problem that labeled conversational negative sample was insufficient. It is important to create an appropriate negative sample automatically because it is too costly to create all possible responses by person and annotate the response's coherence score. To address this problem, we propose a method for generating and labeling feature sensitive negative responses for conversation automatically. Besides, we show that the model learned with the generated negative sample performs well with high correlation between human score and model score.",
keywords = "Conversation, Dialogue, Evaluation, Language Model, Negative Sampling",
author = "Dongjun Kang and Bak, \{Jin Yeong\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Big Data and Smart Computing, BigComp 2023 ; Conference date: 13-02-2023 Through 16-02-2023",
year = "2023",
doi = "10.1109/BigComp57234.2023.00038",
language = "English",
series = "Proceedings - 2023 IEEE International Conference on Big Data and Smart Computing, BigComp 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "183--186",
editor = "Hyeran Byun and Ooi, \{Beng Chin\} and Katsumi Tanaka and Sang-Won Lee and Zhixu Li and Akiyo Nadamoto and Giltae Song and Young-guk Ha and Kazutoshi Sumiya and Wu Yuncheng and Hyuk-Yoon Kwon and Takehiro Yamamoto",
booktitle = "Proceedings - 2023 IEEE International Conference on Big Data and Smart Computing, BigComp 2023",
}