A Simple Contrastive Learning Framework for Interactive Argument Pair Identification via Argument-Context Extraction
Lida Shi, Fausto Giunchiglia, Rui Song, Daqian Shi, Tongtong Liu, Xiaolei Diao, Hao Xu
Abstract
Interactive argument pair identification is an emerging research task for argument mining, aiming to identify whether two arguments are interactively related. It is pointed out that the context of the argument is essential to improve identification performance. However, current context-based methods achieve limited improvements since the entire context typically contains much irrelevant information. In this paper, we propose a simple contrastive learning framework to solve this problem by extracting valuable information from the context. This framework can construct hard argument-context samples and obtain a robust and uniform representation by introducing contrastive learning. We also propose an argument-context extraction module to enhance information extraction by discarding irrelevant blocks. The experimental results show that our method achieves the state-of-the-art performance on the benchmark dataset. Further analysis demonstrates the effectiveness of our proposed modules and visually displays more compact semantic representations.- Anthology ID:
- 2022.emnlp-main.681
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10027–10039
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-main.681
- DOI:
- 10.18653/v1/2022.emnlp-main.681
- Cite (ACL):
- Lida Shi, Fausto Giunchiglia, Rui Song, Daqian Shi, Tongtong Liu, Xiaolei Diao, and Hao Xu. 2022. A Simple Contrastive Learning Framework for Interactive Argument Pair Identification via Argument-Context Extraction. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 10027–10039, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- A Simple Contrastive Learning Framework for Interactive Argument Pair Identification via Argument-Context Extraction (Shi et al., EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2022.emnlp-main.681.pdf