Abstract
We present a simple extension of the GloVe representation learning model that begins with general-purpose representations and updates them based on data from a specialized domain. We show that the resulting representations can lead to faster learning and better results on a variety of tasks.- Anthology ID:
- N18-2034
- Volume:
- Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marilyn Walker, Heng Ji, Amanda Stent
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 212–217
- Language:
- URL:
- https://aclanthology.org/N18-2034
- DOI:
- 10.18653/v1/N18-2034
- Cite (ACL):
- Nicholas Dingwall and Christopher Potts. 2018. Mittens: an Extension of GloVe for Learning Domain-Specialized Representations. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 212–217, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Mittens: an Extension of GloVe for Learning Domain-Specialized Representations (Dingwall & Potts, NAACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/N18-2034.pdf
- Code
- roamanalytics/mittens
- Data
- IMDb Movie Reviews