Learning Sentence Embeddings In The Legal Domain with Low Resource Settings
Sahan Jayasinghe, Lakith Rambukkanage, Ashan Silva, Nisansa de Silva, Shehan Perera, Madhavi Perera
- Anthology ID:
- 2022.paclic-1.55
- Volume:
- Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation
- Month:
- October
- Year:
- 2022
- Address:
- Manila, Philippines
- Editors:
- Shirley Dita, Arlene Trillanes, Rochelle Irene Lucas
- Venue:
- PACLIC
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 494–502
- Language:
- URL:
- https://aclanthology.org/2022.paclic-1.55
- DOI:
- Cite (ACL):
- Sahan Jayasinghe, Lakith Rambukkanage, Ashan Silva, Nisansa de Silva, Shehan Perera, and Madhavi Perera. 2022. Learning Sentence Embeddings In The Legal Domain with Low Resource Settings. In Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation, pages 494–502, Manila, Philippines. Association for Computational Linguistics.
- Cite (Informal):
- Learning Sentence Embeddings In The Legal Domain with Low Resource Settings (Jayasinghe et al., PACLIC 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.paclic-1.55.pdf