Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency

• URL: http://arxiv.org/abs/2306.11550v1
• Date: Mon, 5 Jun 2023 06:53:55 GMT
• Title: Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency
• Authors: Yuxuan Wang, Hong Lyu
• Abstract summary: We show that even a 2-layer, BERT-based query encoder can still retain 92.5% of the full DE performance on the BEIR benchmark. We hope that our findings will encourage the community to re-evaluate the trade-offs between method complexity and performance improvements.
• Score: 4.254906060165999
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The information retrieval community has made significant progress in improving the efficiency of Dual Encoder (DE) dense passage retrieval systems, making them suitable for latency-sensitive settings. However, many proposed procedures are often too complex or resource-intensive, which makes it difficult for practitioners to adopt them or identify sources of empirical gains. Therefore, in this work, we propose a trivially simple recipe to serve as a baseline method for boosting the efficiency of DE retrievers leveraging an asymmetric architecture. Our results demonstrate that even a 2-layer, BERT-based query encoder can still retain 92.5% of the full DE performance on the BEIR benchmark via unsupervised distillation and proper student initialization. We hope that our findings will encourage the community to re-evaluate the trade-offs between method complexity and performance improvements.

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