23.6k citations
- Carnegie Mellon UniversityUS49 papers
- Google (United States)US37 papers
- California Institute of TechnologyUS33 papers
- Amazon (Germany)DE32 papers
- University of Illinois Urbana-ChampaignUS22 papers
- Microsoft (United States)US20 papers
- Stanford UniversityUS20 papers
- The University of Texas at AustinUS20 papers
- University of California, Los AngelesUS20 papers
- University of California, Santa BarbaraUS19 papers
- University of WashingtonUS19 papers
- Georgia Institute of TechnologyUS17 papers
Showing 2024 · cs.IRShow all
3 papers · 2 filters
cs.IR2024★ 1 cited
Towards Robustness Analysis of E-Commerce Ranking System
Ningfei Wang, Yupin Huang, Han Cheng +3
Information retrieval (IR) is a pivotal component in various applications. Recent advances in machine learning (ML) have enabled the integration of ML algorithms into IR, particula…
cs.IR2024★ 5 cited
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce
Nurendra Choudhary, Edward W Huang, Karthik Subbian +1
The problem of search relevance in the E-commerce domain is a challenging one since it involves understanding the intent of a user's short nuanced query and matching it with the ap…
cs.IR2024★ 4 cited
Had enough of experts? Quantitative knowledge retrieval from large language models
David Selby, Kai Spriestersbach, Yuichiro Iwashita +6
Large language models (LLMs) have been extensively studied for their abilities to generate convincing natural language sequences, however their utility for quantitative information…