NumColBERT improves ColBERT performance on numerical query conditions non-intrusively via gating and contrastive learning, outperforming fine-tuning while matching or exceeding separate text-number scoring methods.
Hofstätter, O
3 Pith papers cite this work, alongside 18 external citations. Polarity classification is still indexing.
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A Voronoi cell estimation framework in embedding space enables principled token pruning for late-interaction models, reducing index size while retaining retrieval quality.
Lightweight pooling-aware fine-tuning with k-means on a single dataset enables up to 83% vector compression in ColBERT models with no retrieval accuracy loss and positive cross-dataset transfer.
citing papers explorer
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NumColBERT: Non-Intrusive Numeracy Injection for Late-Interaction Retrieval Models
NumColBERT improves ColBERT performance on numerical query conditions non-intrusively via gating and contrastive learning, outperforming fine-tuning while matching or exceeding separate text-number scoring methods.
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A Voronoi Cell Formulation for Principled Token Pruning in Late-Interaction Retrieval Models
A Voronoi cell estimation framework in embedding space enables principled token pruning for late-interaction models, reducing index size while retaining retrieval quality.
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Learn to Pool: Lightweight Fine-Tuning for Flexible Multi-Vector Compression
Lightweight pooling-aware fine-tuning with k-means on a single dataset enables up to 83% vector compression in ColBERT models with no retrieval accuracy loss and positive cross-dataset transfer.