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        <title>Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency</title>
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%0 Conference Proceedings
%T Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency
%A Wang, Yuxuan
%A Hong, Lyu
%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 wang-hong-2023-query
%R 10.18653/v1/2023.sustainlp-1.23
%U https://aclanthology.org/2023.sustainlp-1.23
%U https://doi.org/10.18653/v1/2023.sustainlp-1.23
%P 290-298

Markdown (Informal)

[Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency](https://aclanthology.org/2023.sustainlp-1.23) (Wang & Hong, sustainlp 2023)

• Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency (Wang & Hong, sustainlp 2023)

ACL

• Yuxuan Wang and Lyu Hong. 2023. Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency. In Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), pages 290–298, Toronto, Canada (Hybrid). Association for Computational Linguistics.