LLM-Alignment Live-Streaming Recommendation
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ID: 283538
2025
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Abstract
In recent years, integrated short-video and live-streaming platforms have
gained massive global adoption, offering dynamic content creation and
consumption. Unlike pre-recorded short videos, live-streaming enables real-time
interaction between authors and users, fostering deeper engagement. However,
this dynamic nature introduces a critical challenge for recommendation systems
(RecSys): the same live-streaming vastly different experiences depending on
when a user watching. To optimize recommendations, a RecSys must accurately
interpret the real-time semantics of live content and align them with user
preferences.
| Reference Key |
zhou2025llmalignment
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|---|---|
| Authors | Yueyang Liu; Jiangxia Cao; Shen Wang; Shuang Wen; Xiang Chen; Xiangyu Wu; Shuang Yang; Zhaojie Liu; Kun Gai; Guorui Zhou |
| Journal | arXiv |
| Year | 2025 |
| DOI |
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