- Anthology ID:
- 2023.sustainlp-1.23
- Volume:
- Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada (Hybrid)
- Editors:
- Nafise Sadat Moosavi, Iryna Gurevych, Yufang Hou, Gyuwan Kim, Young Jin Kim, Tal Schuster, Ameeta Agrawal
- Venue:
- sustainlp
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 290–298
- Language:
- URL:
- https://aclanthology.org/2023.sustainlp-1.23
- DOI:
- 10.18653/v1/2023.sustainlp-1.23
- Cite (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.
- Cite (Informal):
- Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency (Wang & Hong, sustainlp 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.sustainlp-1.23.pdf