Toward Better Storylines with Sentence-Level Language Models
Daphne Ippolito, David Grangier, Douglas Eck, Chris Callison-Burch
Abstract
We propose a sentence-level language model which selects the next sentence in a story from a finite set of fluent alternatives. Since it does not need to model fluency, the sentence-level language model can focus on longer range dependencies, which are crucial for multi-sentence coherence. Rather than dealing with individual words, our method treats the story so far as a list of pre-trained sentence embeddings and predicts an embedding for the next sentence, which is more efficient than predicting word embeddings. Notably this allows us to consider a large number of candidates for the next sentence during training. We demonstrate the effectiveness of our approach with state-of-the-art accuracy on the unsupervised Story Cloze task and with promising results on larger-scale next sentence prediction tasks.- Anthology ID:
- 2020.acl-main.666
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 7472–7478
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.666
- DOI:
- 10.18653/v1/2020.acl-main.666
- Cite (ACL):
- Daphne Ippolito, David Grangier, Douglas Eck, and Chris Callison-Burch. 2020. Toward Better Storylines with Sentence-Level Language Models. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7472–7478, Online. Association for Computational Linguistics.
- Cite (Informal):
- Toward Better Storylines with Sentence-Level Language Models (Ippolito et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/2020.acl-main.666.pdf
- Code
- google-research/google-research