4 upvotes
Trainable Prefix Tokens Clean Up Retrieval Embeddings
What is Reducing Representational Interference in Retrieval Embeddings with Trainable Prefix Tokens?
The paper adds a few learnable tokens before each input text, letting the model separate true meaning from stray token-level artifacts. This simple prefix reduces interference and yields sharper, more reliable vectors for similarity search.
Who it is for
Anyone building or fine-tuning dense retrieval or vector-search pipelines can adopt the prefix trick to boost embedding quality without redesigning the whole model.