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20212024
most citedRethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models

3 citations · 3 across the 9 of their papers we have counts for

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cs.IR2024

Domain-Aware Cross-Attention for Cross-domain Recommendation

Yuhao Luo, Shiwei Ma, Mingjun Nie +4

Cross-domain recommendation (CDR) is an important method to improve recommender system performance, especially when observations in target domains are sparse. However, most existin…

cs.IR2023

An Incremental Update Framework for Online Recommenders with Data-Driven Prior

Chen Yang, Jin Chen, Qian Yu +10

Online recommenders have attained growing interest and created great revenue for businesses. Given numerous users and items, incremental update becomes a mainstream paradigm for le…

cs.IR2023

Parallel Ranking of Ads and Creatives in Real-Time Advertising Systems

Zhiguang Yang, Lu Wang, Chun Gan +7

"Creativity is the heart and soul of advertising services". Effective creatives can create a win-win scenario: advertisers can reach target users and achieve marketing objectives m…

cs.IR20233 cited

Rethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models

Jinbo Song, Ruoran Huang, Xinyang Wang +9

Industrial systems such as recommender systems and online advertising, have been widely equipped with multi-stage architectures, which are divided into several cascaded modules, in…

cs.IR2023

Towards Better Query Classification with Multi-Expert Knowledge Condensation in JD Ads Search

Kun-Peng Ning, Ming Pang, Zheng Fang +6

Search query classification, as an effective way to understand user intents, is of great importance in real-world online ads systems. To ensure a lower latency, a shallow model (e.…

cs.IR2022

Gating-adapted Wavelet Multiresolution Analysis for Exposure Sequence Modeling in CTR prediction

Xiaoxiao Xu, Zhiwei Fang, Qian Yu +7

The exposure sequence is being actively studied for user interest modeling in Click-Through Rate (CTR) prediction. However, the existing methods for exposure sequence modeling brin…