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Research·arXiv cs.CL·

Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference

Illustration accompanying: Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference

Researchers propose a diagnostic framework for ColBERT and other late-interaction retrieval models, using learned latent spaces to surface systematic failures in biomedical ranking tasks. The work addresses a gap in model interpretability: while token-level scores explain individual rankings, they don't reveal whether models reliably understand clinical concepts across varied phrasings.

MentionsColBERT

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Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference · Modelwire