IRRGN: An Implicit Relational Reasoning Graph Network for Multi-turn Response Selection

Jingcheng Deng, Hengwei Dai, Xuewei Guo, Yuanchen Ju, Wei Peng

Abstract
The task of response selection in multi-turn dialogue is to find the best option from all candidates. In order to improve the reasoning ability of the model, previous studies pay more attention to using explicit algorithms to model the dependencies between utterances, which are deterministic, limited and inflexible. In addition, few studies consider differences between the options before and after reasoning. In this paper, we propose an Implicit Relational Reasoning Graph Network to address these issues, which consists of the Utterance Relational Reasoner (URR) and the Option Dual Comparator (ODC). URR aims to implicitly extract dependencies between utterances, as well as utterances and options, and make reasoning with relational graph convolutional networks. ODC focuses on perceiving the difference between the options through dual comparison, which can eliminate the interference of the noise options. Experimental results on two multi-turn dialogue reasoning benchmark datasets MuTual and MuTualplus show that our method significantly improves the baseline of four pre-trained language models and achieves state-of-the-art performance. The model surpasses human performance for the first time on the MuTual dataset.
Anthology ID:
2022.emnlp-main.584
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8529–8541
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URL:
https://aclanthology.org/2022.emnlp-main.584
DOI:
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Cite (ACL):
Jingcheng Deng, Hengwei Dai, Xuewei Guo, Yuanchen Ju, and Wei Peng. 2022. IRRGN: An Implicit Relational Reasoning Graph Network for Multi-turn Response Selection. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 8529–8541, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
IRRGN: An Implicit Relational Reasoning Graph Network for Multi-turn Response Selection (Deng et al., EMNLP 2022)
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