14 citations · 19 across the 3 of their papers we have counts for
3 papers
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★ 14 cited
Enhancing Relevance of Embedding-based Retrieval at Walmart
Juexin Lin, Sachin Yadav, Feng Liu +8
Embedding-based neural retrieval (EBR) is an effective search retrieval method in product search for tackling the vocabulary gap between customer search queries and products. The i…
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…