10 citations · 12 across the 6 of their papers we have counts for
6 papers
Semantic Retrieval at Walmart
Alessandro Magnani, Feng Liu, Suthee Chaidaroon +8
In product search, the retrieval of candidate products before re-ranking is more critical and challenging than other search like web search, especially for tail queries, which have…
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…
Overview of the TREC 2023 Product Product Search Track
Daniel Campos, Surya Kallumadi, Corby Rosset +2
This is the first year of the TREC Product search track. The focus this year was the creation of a reusable collection and evaluation of the impact of the use of metadata and multi…
Quick Dense Retrievers Consume KALE: Post Training Kullback Leibler Alignment of Embeddings for Asymmetrical dual encoders
Daniel Campos, Alessandro Magnani, ChengXiang Zhai
In this paper, we consider the problem of improving the inference latency of language model-based dense retrieval systems by introducing structural compression and model size asymm…
Noise-Robust Dense Retrieval via Contrastive Alignment Post Training
Daniel Campos, ChengXiang Zhai, Alessandro Magnani
The success of contextual word representations and advances in neural information retrieval have made dense vector-based retrieval a standard approach for passage and document rank…
Is a picture worth a thousand words? A Deep Multi-Modal Fusion Architecture for Product Classification in e-commerce
Tom Zahavy, Alessandro Magnani, Abhinandan Krishnan +1
Classifying products into categories precisely and efficiently is a major challenge in modern e-commerce. The high traffic of new products uploaded daily and the dynamic nature of…