POS-Constrained Parallel Decoding for Non-autoregressive Generation

Kexin Yang, Wenqiang Lei, Dayiheng Liu, Weizhen Qi, Jiancheng Lv


Abstract
The multimodality problem has become a major challenge of existing non-autoregressive generation (NAG) systems. A common solution often resorts to sequence-level knowledge distillation by rebuilding the training dataset through autoregressive generation (hereinafter known as “teacher AG”). The success of such methods may largely depend on a latent assumption, i.e., the teacher AG is superior to the NAG model. However, in this work, we experimentally reveal that this assumption does not always hold for the text generation tasks like text summarization and story ending generation. To provide a feasible solution to the multimodality problem of NAG, we propose incorporating linguistic structure (Part-of-Speech sequence in particular) into NAG inference instead of relying on teacher AG. More specifically, the proposed POS-constrained Parallel Decoding (POSPD) method aims at providing a specific POS sequence to constrain the NAG model during decoding. Our experiments demonstrate that POSPD consistently improves NAG models on four text generation tasks to a greater extent compared to knowledge distillation. This observation validates the necessity of exploring the alternatives for sequence-level knowledge distillation.
Anthology ID:
2021.acl-long.467
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5990–6000
Language:
URL:
https://aclanthology.org/2021.acl-long.467
DOI:
10.18653/v1/2021.acl-long.467
Bibkey:
Cite (ACL):
Kexin Yang, Wenqiang Lei, Dayiheng Liu, Weizhen Qi, and Jiancheng Lv. 2021. POS-Constrained Parallel Decoding for Non-autoregressive Generation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 5990–6000, Online. Association for Computational Linguistics.
Cite (Informal):
POS-Constrained Parallel Decoding for Non-autoregressive Generation (Yang et al., ACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-long.467.pdf
Video:
 https://aclanthology.org/2021.acl-long.467.mp4
Code
 yangkexin/pospd
Data
GLGEROCStories