Abstract
This tutorial discusses cutting-edge research on NLI, including recent advance on dataset development, cutting-edge deep learning models, and highlights from recent research on using NLI to understand capabilities and limits of deep learning models for language understanding and reasoning.- Anthology ID:
- N19-5002
- Volume:
- Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorials
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 6–8
- Language:
- URL:
- https://aclanthology.org/N19-5002
- DOI:
- 10.18653/v1/N19-5002
- Cite (ACL):
- Samuel Bowman and Xiaodan Zhu. 2019. Deep Learning for Natural Language Inference. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorials, pages 6–8, Minneapolis, Minnesota. Association for Computational Linguistics.
- Cite (Informal):
- Deep Learning for Natural Language Inference (Bowman & Zhu, NAACL 2019)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/N19-5002.pdf
- Data
- MultiNLI