9 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.IR2026
Query Generation with Direct Preference Optimization for Document Expansion in E-commerce Search
Kaihao Li, Feng Liu, Juexin Lin +4
Doc2Query, a popular document expansion technique, leverages sequence-to-sequence models to generate relevant queries, effectively addressing the "vocabulary mismatch" problem in i…
cs.IR2026
Scaling and Stabilizing Large-Scale Embedding-Based Retrieval
Zhen Yang, Juexin Lin, Hongwei Shang +8
Embedding-based retrieval (EBR) is foundational to large-scale e-commerce search, yet its effectiveness is often constrained by the quality of training signals and the representati…
cs.IR2024★ 9 cited
Relevance Filtering for Embedding-based Retrieval
Nicholas Rossi, Juexin Lin, Feng Liu +4
In embedding-based retrieval, Approximate Nearest Neighbor (ANN) search enables efficient retrieval of similar items from large-scale datasets. While maximizing recall of relevant…