Papers with late interaction

2 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.
LILaC: Late Interacting in Layered Component Graph for Open-domain Multimodal Multihop Retrieval (2025.emnlp-main)

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Challenge: Existing multimodal document retrieval frameworks focus on textual, tabular, and visual elements, but there is a shift toward open-domain multimodal retrieval.
Approach: They propose a multimodal retrieval framework that uses a component graph and a late-interaction-based subgraph retrieval method to capture semantic relationships between components.
Outcome: The proposed framework achieves state-of-the-art retrieval performance on all five benchmarks . it is based on a layered component graph representing multimodal information at two layers .

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