Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers
Sentence Transformers has released the Multi-Vector (Late Interaction) embedding model, aimed at improving the quality of semantic representations through a late interaction mechanism. This model encodes sentences after segmenting them, and then fuses them in a vector space to enhance the ability to capture long-distance dependencies. Experiments show that this method outperforms traditional single-vector methods in multiple benchmark tests, effectively improving the performance of retrieval and classification tasks.