Mustafa Canim

Do Retrieval-Trained Embeddings Help Linear Contextual Bandits?

Text embeddings from retrieval-tuned (dual-encoder) models are increasingly used as context features in contextual bandits for recommendation, on the assumption that an embedding space optimized for inner-product similarity will speed up a linear exploration policy. This study tests that assumption with a controlled, s...