Lightweight Pooling Fine-Tuning Achieves Lossless Compression for ColBERT
_reachsumit · x · 2026-07-08
Research shows that introducing k-means pooling-aware fine-tuning (requiring only lightweight training) enables multi-vector retrieval models like ColBERT to drastically compress the number of vectors with zero accuracy loss. This method offers a low-cost, flexible compression solution for deploying multi-vector retrieval in storage- and latency-constrained environments.
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