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20242026
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cs.IR2026

From Trajectories to Evidence: Auditable Experimental Records for Industrial Research Agents

Zijie Zhuang, Changxin Lao, Pengbo Xu +13

Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings and retain the resulting trajectories to guide later decisions.…

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.IR2026

Break the Inaccessible Boundary: Distilling Post-Conversion Content for User Retention Modeling

Tianbao Ma, Ruochen Yang, Chengen Li +7

User retention is a key metric to measure long-term engagement in modern platforms. In real-time bidding (RTB) advertising system for user re-engagement, the retention model is req…

cs.IR2026

Harmonizing Generative Retrieval and Ranking in Chain-of-Recommendation

Yu Liu, Jiangxia Cao

Generative recommender systems have recently emerged as a promising paradigm by formulating next-item prediction as an auto-regressive semantic IDs generation, such as OneRec serie…

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

OneLive: Dynamically Unified Generative Framework for Live-Streaming Recommendation

Shen Wang, Yusheng Huang, Ruochen Yang +15

Live-streaming recommender system serves as critical infrastructure that bridges the patterns of real-time interactions between users and authors. Similar to traditional industrial…