Generative recommendation, has been attracted a surge of attentions in industrial and academic research community, towards to build more smart system to build next-generation recommender. Under the significant developing wave of large language model, our team have been developed Semantic ID based OneRec/OneRec-V2. Thes...
Jiang-Xia Cao, Hao Peng, Wen-Long Xu et al.· 0 citations
Generative recommendation reformulates sequential recommendation as autoregressive generation by encoding items into semantic tokens, enabling improved scaling capability and cross-domain generalization. However, existing generative recommender systems typically follow a two-stage pipeline, where item tokenization is l...
Jia-Yi Dan, Wei-Jian Li, Yong-Qi Liu et al.· Proceedings of the 20th ACM...· 0 citations
This work proposes OGR, an end-to-end framework that directly generates ordered slates-"Once Generated, Ranked" and proposes SPA, a reward-guided conservative policy optimization method that aligns generated slates with user preferences beyond likelihood imitation.
CineForge is introduced, a self-evolving video-production agent framework that couples CineForge-Produce for video generation with CineForge-Evolve for cross-story policy evolution, and CineForge-Evolve applies Case-to-Pattern-to-Policy Evolution to review trajectory evidence, consolidate recurrent findings into bounde...
Jun-Xiang Liu, Lin Wang, Haitian Shi et al.· 0 citations
SWIM (Step-Wise Integrated Measure), a list-level evaluator that models user behaviors as a finite-horizon prefix session-level survival process, and efficiently estimates continuation probabilities and utilities in parallel, satisfying strict industrial latency constraints.
Yuan Pu, Chenghao Zhang, Chao Feng et al.· 0 citations
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