4 citations · 5 across the 3 of their papers we have counts for
3 papers
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.IR2025★ 4 cited
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,…
cs.IR2024★ 1 cited
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…