11 citations · 22 across the 13 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.IR2024
RecSys Arena: Pair-wise Recommender System Evaluation with Large Language Models
Zhuo Wu, Qinglin Jia, Chuhan Wu +4
Evaluating the quality of recommender systems is critical for algorithm design and optimization. Most evaluation methods are computed based on offline metrics for quick algorithm e…
cs.IR2024
Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation
Yuang Zhao, Zhaocheng Du, Qinglin Jia +3
With the increase in the business scale and number of domains in online advertising, multi-domain ad recommendation has become a mainstream solution in the industry. The core of mu…
cs.LG2024
Confidence-Aware Multi-Field Model Calibration
Yuang Zhao, Chuhan Wu, Qinglin Jia +6
Accurately predicting the probabilities of user feedback, such as clicks and conversions, is critical for advertisement ranking and bidding. However, there often exist unwanted mis…