2025
Search Query Embeddings via User-behavior-driven Contrastive Learning
NAACL 2025industry
Universal query embeddings that accurately capture the semantic meaning of search queries are crucial for supporting a range of query understanding (QU) tasks within enterprises.However, current embedding approaches often struggle to effectively represent queries due to the shortness of search queri…