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UniRec: Cross-stage Multi-Task Fusion with Preference Alignment for Cascaded Recommender Systems
Lingyuan Kong, Jiaqi Cui, Fanjiao Zeng +6
Industrial recommender systems cascade stages with different objectives, feature spaces, and latency constraints. Optimizing pre-ranking and ranking separately induces cross-stage…
CineForge: Self-Improving Agents for Long-Horizon Video Generation
Junxiang Liu, Lin Wang, Haiyu Shi +10
Long-horizon story-driven video generation requires a production agent to coordinate narrative decomposition, state tracking, shot design, prompt construction, rendering, and revis…
SWIM: Step-Wise Integrated Measure for Session-supervised List Evaluation in Generative Re-ranking
Yuanhao Pu, Chenghao Zhang, Chao Feng +6
Modern industrial recommender systems have increasingly adopted the Generator-Evaluator (G-E) framework for the re-ranking stage. Within this paradigm, the generator produces candi…
Once Generated, Ranked: End-to-End Generative Slate Recommendation with Unified Semantic-Collaborative IDs
Yang Hu, Jiayi Guo, Jingui Ma +6
Slate recommendation treats a slate rather than an individual item as the recommendation unit, requiring joint optimization of item interactions and slate utility. Existing approac…
DrEM: Dual-Side Robust Ensemble Ranking from Noisy User Preference Predictions in Video Recommendation
Canwei Huang, Tiantian He, Xiaoxiao Xu +5
Industrial video recommendation systems typically adopt a multi-stage architecture. At the ensemble ranking stage, multi-dimensional user preference predictions (pxtrs) from an ups…
Uncertainty as Remedy: Mitigating Satisfaction Label Bias in Short Video Multi-Objective Ensemble Ranking
Zonghe Shao, Tiantian He, Xiaoxiao Xu +6
The core objective of short video recommendation is to model users' unobservable true satisfaction with recommended videos. As the dominant industrial framework, end-to-end multi-o…