Learning to Write with Cooperative Discriminators

Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub, Yejin Choi


Abstract
Despite their local fluency, long-form text generated from RNNs is often generic, repetitive, and even self-contradictory. We propose a unified learning framework that collectively addresses all the above issues by composing a committee of discriminators that can guide a base RNN generator towards more globally coherent generations. More concretely, discriminators each specialize in a different principle of communication, such as Grice’s maxims, and are collectively combined with the base RNN generator through a composite decoding objective. Human evaluation demonstrates that text generated by our model is preferred over that of baselines by a large margin, significantly enhancing the overall coherence, style, and information of the generations.
Anthology ID:
P18-1152
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1638–1649
Language:
URL:
https://aclanthology.org/P18-1152
DOI:
10.18653/v1/P18-1152
Bibkey:
Cite (ACL):
Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub, and Yejin Choi. 2018. Learning to Write with Cooperative Discriminators. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1638–1649, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Learning to Write with Cooperative Discriminators (Holtzman et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-1152.pdf
Note:
 P18-1152.Notes.pdf
Poster:
 P18-1152.Poster.pdf
Code
 additional community code
Data
BookCorpusMultiNLISNLI