CoLo: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization
Chenxin An, Ming Zhong, Zhiyong Wu, Qin Zhu, Xuanjing Huang, Xipeng Qiu
Abstract
Traditional training paradigms for extractive and abstractive summarization systems always only use token-level or sentence-level training objectives. However, the output summary is always evaluated from summary-level which leads to the inconsistency in training and evaluation. In this paper, we propose a Contrastive Learning based re-ranking framework for one-stage summarization called CoLo. By modeling a contrastive objective, we show that the summarization model is able to directly generate summaries according to the summary-level score without additional modules and parameters. Extensive experiments demonstrate that CoLo boosts the extractive and abstractive results of one-stage systems on CNN/DailyMail benchmark to 44.58 and 46.33 ROUGE-1 score while preserving the parameter efficiency and inference efficiency. Compared with state-of-the-art multi-stage systems, we save more than 100 GPU training hours and obtaining 3x 8x speed-up ratio during inference while maintaining comparable results.- Anthology ID:
- 2022.coling-1.508
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 5783–5793
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.508
- DOI:
- Cite (ACL):
- Chenxin An, Ming Zhong, Zhiyong Wu, Qin Zhu, Xuanjing Huang, and Xipeng Qiu. 2022. CoLo: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization. In Proceedings of the 29th International Conference on Computational Linguistics, pages 5783–5793, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- CoLo: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization (An et al., COLING 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2022.coling-1.508.pdf
- Code
- chenxinan-fdu/colo
- Data
- CNN/Daily Mail, SSN