12 papers
EvoReason: Self-Evolving Reasoning Primitive-Guided On-Policy Distillation for Latent Reasoning in Generative Recommendation
Zhuang Zhuang, Zhipeng Wei, Rongfeng Guo +4
Generative recommendation benefits from reasoning-enhanced inference, and latent reasoning offers an efficient paradigm by encoding intermediate reasoning processes into compact co…
Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation
Long Zhang, Hao Jiang, Sheng Yu +3
While large language models (LLMs) have advanced ID-based recommendation through Semantic ID (SID) modeling, existing SID generation frameworks largely follow a single-representati…
From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation
Zhi Chen, Minmao Wang, Xingchen Liu +8
The paper introduces a feedback‑driven framework that first extracts user intent and then discovers recommendation policies using outcome‑derived feedback, distilling this knowledg…
WhisperRec: Latent Reasoning for Efficient Foundation Recommendation Models
Hao Jiang, Peiru Du, Pengfei Yao +10
The paper presents WhisperRec, a framework that compresses teacher-generated chain‑of‑thought explanations into learnable latent tokens, allowing recommendation models to reason in…
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…
SinkRec: Mitigating Semantic State Sink in Long Sequence Recommendation with Memory-Conditioned Gated Delta Networks
Zhuang Zhuang, Zhipeng Wei, Ji Dai +4
Linear attention provides an efficient backbone for long-sequence recommendation by avoiding the quadratic cost of standard Transformers, but its compressed recurrent state can be…