most citedCapturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach

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cs.IR2026

WhisperRec: Latent Reasoning for Efficient Foundation Recommendation Models

Hao Jiang, Peiru Du, Pengfei Yao +10

Large language models (LLMs) have demonstrated strong reasoning capabilities, motivating their adoption as backbones for foundation recommendation models (FRMs). Existing approache…

cs.IR2026

POEM: Partial-Order Enhanced Real-Time Sequential Modeling for Recommendation

Linxiao Che, Yijia Sun, Siyuan Lou +5

Real-time recommendation systems suffer from the dynamic drift of user interests and varying contextual conditions. Conventional sequential recommendation models only exploit stati…

cs.IR2026

OneReason Technical Report

OneRec Team, Biao Yang, Boyang Ding +81

Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…

cs.IR2023★ 1 cited

Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach

Zhangming Chan, Yu Zhang, Shuguang Han +8

Conversion rate (CVR) prediction is one of the core components in online recommender systems, and various approaches have been proposed to obtain accurate and well-calibrated CVR e…

cs.IR2023

COPR: Consistency-Oriented Pre-Ranking for Online Advertising

Zhishan Zhao, Jingyue Gao, Yu Zhang +8

Cascading architecture has been widely adopted in large-scale advertising systems to balance efficiency and effectiveness. In this architecture, the pre-ranking model is expected t…