Token Pooling-Aware Training for Multi-Vector Embedding Models

The article discusses the implementation of token pooling-aware training for multi-vector embedding models, which allows for better information retention while reducing the number of document vectors. The method improves the retention of relevant information during vector compression, achieving a retention rate of 97.8% at a 4x reduction in document vectors.