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%0 Conference Proceedings
%T Learning Sentence Embeddings In The Legal Domain with Low Resource Settings
%A Jayasinghe, Sahan
%A Rambukkanage, Lakith
%A Silva, Ashan
%A de Silva, Nisansa
%A Perera, Shehan
%A Perera, Madhavi
%Y Dita, Shirley
%Y Trillanes, Arlene
%Y Lucas, Rochelle Irene
%S Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation
%D 2022
%8 October
%I Association for Computational Linguistics
%C Manila, Philippines
%F jayasinghe-etal-2022-learning
%U https://aclanthology.org/2022.paclic-1.55
%P 494-502

Markdown (Informal)

[Learning Sentence Embeddings In The Legal Domain with Low Resource Settings](https://aclanthology.org/2022.paclic-1.55) (Jayasinghe et al., PACLIC 2022)

• Learning Sentence Embeddings In The Legal Domain with Low Resource Settings (Jayasinghe et al., PACLIC 2022)

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.