Adversarial Multi-task Learning for Text Classification
Published in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017
Recommended citation: Pengfei Liu, Xipeng Qiu, Xuanjing Huang: Adversarial Multi-task Learning for Text Classification. ACL (1) 2017: 1-10 http://xuanjing-huang.github.io/files/AMT.pdf
Neural network models have shown their promising opportunities for multi-task learning, which focus on learning the shared layers to extract the common and task-invariant features. However, in most existing approaches, the extracted shared features are prone to be contaminated by task-specific features or the noise brought by other tasks. In this paper, we propose an adversarial multi-task learning framework, alleviating the shared and private latent feature spaces from interfering with each other.