ColBERTSaR: Sparsified ColBERT Index via Product Quantization 事件

ColBERTSaR: Sparsified ColBERT Index via Product Quantization arXiv:2606.05568v1 Announce Type: cross Abstract: While ColBERT is an effective neural retrieval architecture, it requires a heavy index structure to support candidate set retrieval based on approximated token embeddings, gathering and decompressing document token embeddings, and applying the MaxSim operation. Indexes in PLAID and similar ColBERT implementations require five to ten times the disk storage of the original raw text, whi