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cs.IR2026

SARM: LLM-Augmented Semantic Anchor for End-to-End Live-Streaming Ranking

Ruochen Yang, Yueyang Liu, Zijie Zhuang +14

Large-scale live-streaming recommendation requires precise modeling of non-stationary content semantics under strict real-time serving constraints. In industrial deployment, two co…

cs.IR2026

QARM V2: Quantitative Alignment Multi-Modal Recommendation for Reasoning User Sequence Modeling

Tian Xia, Jiaqi Zhang, Yueyang Liu +25

With the evolution of large language models (LLMs), there is growing interest in leveraging their rich semantic understanding to enhance industrial recommendation systems (RecSys).…

cs.IR2025

Foresight Prediction Enhanced Live-Streaming Recommendation

Jiangxia Cao, Ruochen Yang, Xiang Chen +8

Live-streaming, as an emerging media enabling real-time interaction between authors and users, has attracted significant attention. Unlike the stable playback time of traditional T…

cs.IR2025

Multimodal Recommendation via Self-Corrective Preference Alignmen

Yalong Guan, Xiang Chen, Mingyang Wang +7

With the rapid growth of live streaming platforms, personalized recommendation systems have become pivotal in improving user experience and driving platform revenue. The dynamic an…

cs.IR2025

LLM-Alignment Live-Streaming Recommendation

Yueyang Liu, Jiangxia Cao, Shen Wang +7

In recent years, integrated short-video and live-streaming platforms have gained massive global adoption, offering dynamic content creation and consumption. Unlike pre-recorded sho…