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Rethinking Latent Reasoning for Generative Recommendation: Beyond Teacher-Generated CoT and Recurrent Hidden-State Feedback

Yiwen Chen, Fuwei Zhang, Zehao Chen, Deqing Wang, Hehan Li, Peizhi Xu, Hanmeng Liu, Shuanglong Li, Xin Pei, Fuzhen Zhuang, Zhao Zhang

Adds learned thought tokens between a user’s item history and the next-item prediction. Trains their hidden states to represent keywords from past items, then processes all thought tokens in one prompt pass without generating a written reasoning trace.

First public: · Added to this list: November 9, 2026

Cite this paper

ArXiv preprint

arXiv:2611.09006 · Initial submission: 2026-11-06

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Explore this approach

Thinking tokens — Give a model extra tokens for computation, such as pauses, filler symbols, or learned planning tokens. These tokens need not spell out the solution.