4 citations · 5 across the 3 of their papers we have counts for
4 papers · 1 filter
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…
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…
Knowledge Distillation for Enhancing Walmart E-commerce Search Relevance Using Large Language Models
Hongwei Shang, Nguyen Vo, Nitin Yadav +6
Ensuring the products displayed in e-commerce search results are relevant to users queries is crucial for improving the user experience. With their advanced semantic understanding,…
Large Language Models for Relevance Judgment in Product Search
Navid Mehrdad, Hrushikesh Mohapatra, Mossaab Bagdouri +8
High relevance of retrieved and re-ranked items to the search query is the cornerstone of successful product search, yet measuring relevance of items to queries is one of the most…