8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.IR2026
Atomic Information Flow: A Network Flow Model for Tool Attributions in RAG Systems
James Gao, Josh Zhou, Qi Sun +2
Many tool-based Retrieval Augmented Generation (RAG) systems lack precise mechanisms for tracing final responses back to specific tool components -- a critical gap as systems scale…
cs.LG2020
Automatic Historical Feature Generation through Tree-based Method in Ads Prediction
Hongjian Wang, Qi Li, Lanbo Zhang +4
Historical features are important in ads click-through rate (CTR) prediction, because they account for past engagements between users and ads. In this paper, we study how to effici…
stat.ML2019★ 8 cited
Addressing Delayed Feedback for Continuous Training with Neural Networks in CTR prediction
Sofia Ira Ktena, Alykhan Tejani, Lucas Theis +5
One of the challenges in display advertising is that the distribution of features and click through rate (CTR) can exhibit large shifts over time due to seasonality, changes to ad…