Papers with aggressive residual compression mechanism

1 papers
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction (2022.naacl-main)

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Challenge: Neural information retrieval (IR) methods encode queries and documents into single vectors, but late interaction models produce multi-vector representations at the granularity of each token.
Approach: They propose a retrieval method that couples an aggressive residual compression mechanism with a denoised supervision strategy to improve the quality and space footprint of late interaction.
Outcome: The proposed retriever improves quality and space footprint of late interaction models while reducing space footprint by 6–10x.

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