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EigenLI framework offers spectral approximation for late-interaction models

By PulseAugur Editorial · [2 sources] ·

Researchers have developed EigenLI, a novel framework for approximating late-interaction models in information retrieval. This method leverages the intrinsic low-rank structure of document token embeddings to compress representations, significantly reducing indexing costs and storage footprints. EigenLI identifies dominant eigendirections within documents to create reduced interaction representations, outperforming traditional clustering and pooling methods in empirical tests. AI

IMPACT This research could lead to more efficient and cost-effective information retrieval systems by reducing computational and storage overhead.

RANK_REASON The cluster contains an academic paper detailing a new framework for information retrieval models.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

EigenLI framework offers spectral approximation for late-interaction models

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The cluster contains an academic paper detailing a new framework for information retrieval models.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Archish S, Sabyasachi Basu, Ankit Garg, Ravishankar Krishnaswamy, Kirankumar Shiragur ·

    EigenLI: Spectral Approximations to Late Interaction

    arXiv:2609.07561v1 Announce Type: cross Abstract: Late-interaction models such as ColBERT achieve strong effectiveness by representing each document with many token-level vectors, but this expressivity leads to large indexing cost, storage footprints and expensive MaxSim scoring.…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Kirankumar Shiragur ·

    EigenLI: Spectral Approximations to Late Interaction

    Late-interaction models such as ColBERT achieve strong effectiveness by representing each document with many token-level vectors, but this expressivity leads to large indexing cost, storage footprints and expensive MaxSim scoring. We show that late-interaction representations exh…

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