3 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
Towards More Relevant Product Search Ranking Via Large Language Models: An Empirical Study
Qi Liu, Atul Singh, Jingbo Liu +2
Training Learning-to-Rank models for e-commerce product search ranking can be challenging due to the lack of a gold standard of ranking relevance. In this paper, we decompose ranki…
Long or Short or Both? An Exploration on Lookback Time Windows of Behavioral Features in Product Search Ranking
Qi Liu, Atul Singh, Jingbo Liu +3
Customer shopping behavioral features are core to product search ranking models in eCommerce. In this paper, we investigate the effect of lookback time windows when aggregating the…
LLM360: Towards Fully Transparent Open-Source LLMs
Zhengzhong Liu, Aurick Qiao, Willie Neiswanger +25
The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs…