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Exciting addition coming with the next txtai release: LEMUR for ColBERT-style Late-Interaction Retrieval! π
Contributor @Morgan-coded introduced LEMUR to txtai, making it, as far as we know, the first framework to incorporate LEMUR for late-interaction retrieval using standard, fixed-vector indexes.
Key benefits:
π Significant boost: 49β62% higher NDCG@10 than 2,048-dimensional MUVERA
πΎ 5x less storage: 2,048 dimensions vs. MUVERAβs default 10,240
π Better geometry: Optional batch mean centering addresses anisotropy in token embeddings
A promising step toward making ColBERT-style retrieval more practical with conventional vector search.
Read the full breakdown: https://huggingface.co/blog/NeuML/txtai-lemur
Contributor @Morgan-coded introduced LEMUR to txtai, making it, as far as we know, the first framework to incorporate LEMUR for late-interaction retrieval using standard, fixed-vector indexes.
Key benefits:
π Significant boost: 49β62% higher NDCG@10 than 2,048-dimensional MUVERA
πΎ 5x less storage: 2,048 dimensions vs. MUVERAβs default 10,240
π Better geometry: Optional batch mean centering addresses anisotropy in token embeddings
A promising step toward making ColBERT-style retrieval more practical with conventional vector search.
Read the full breakdown: https://huggingface.co/blog/NeuML/txtai-lemur