The proposed OneModel, a unified framework for multi-stream final ranking, maps heterogeneous behaviors into shared event sequences, learns long-context user representations with an action-oriented backbone, and introduces scenario-aware Information Modulation to balance cross-stream transfer and stream-specific specia...
Yinqi Zhang, Pei-Yu Hu, Yuntian Tang et al.· 1 citation
Experiments show that \textsc{AtomRec} consistently outperforms state-of-the-art agentic and memory-augmented baselines, with around 8.5\% average relative improvement across metrics.
Pei-Yu Hu, Wei-Hai Lu, Si-Ying Gu et al.· 0 citations
To further optimize the reasoning trajectory, HiLaR combines final recommendation feedback with layer-aware process rewards derived from the marginal target-likelihood gain of each state, and generally outperforms strong sequential, generative, and LLM-based recommendation baselines.
Pei-Yu Hu, Si-Ying Gu, Wei-Hai Lu et al.· arXiv.org· 1 citation
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