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%0 Conference Proceedings
%T Quick Dense Retrievers Consume KALE: Post Training KullbackLeibler Alignment of Embeddings for Asymmetrical dual encoders
%A Campos, Daniel
%A Magnani, Alessandro
%A Zhai, Chengxiang
%Y Sadat Moosavi, Nafise
%Y Gurevych, Iryna
%Y Hou, Yufang
%Y Kim, Gyuwan
%Y Kim, Young Jin
%Y Schuster, Tal
%Y Agrawal, Ameeta
%S Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada (Hybrid)
%F campos-etal-2023-quick
%R 10.18653/v1/2023.sustainlp-1.4
%U https://aclanthology.org/2023.sustainlp-1.4
%U https://doi.org/10.18653/v1/2023.sustainlp-1.4
%P 59-77

Markdown (Informal)

[Quick Dense Retrievers Consume KALE: Post Training KullbackLeibler Alignment of Embeddings for Asymmetrical dual encoders](https://aclanthology.org/2023.sustainlp-1.4) (Campos et al., sustainlp 2023)

• Quick Dense Retrievers Consume KALE: Post Training KullbackLeibler Alignment of Embeddings for Asymmetrical dual encoders (Campos et al., sustainlp 2023)

ACL

• Daniel Campos, Alessandro Magnani, and Chengxiang Zhai. 2023. Quick Dense Retrievers Consume KALE: Post Training KullbackLeibler Alignment of Embeddings for Asymmetrical dual encoders. In Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), pages 59–77, Toronto, Canada (Hybrid). Association for Computational Linguistics.