arXiv 2610.20951 · cs.AI · 2026-10-14
LEV: Thinking Fast and Deep with Looped Decision Models
Dingjie Song, Zhiling Yan, Yuxuan Zhang, Lichao Sun
机构待核实
在最新榜 #30 2026-W43 第 2 名（进行中） 本站收录于 2026-10-21
一句话要点
LEV 让决策模型通过循环重跑网络层来“想得更深”，不必生成推理文字。
LEV lets decision models think deeper by looping their layers instead of generating reasoning tokens.
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主题与学科
同主题：推理
- Thinking Inertia: LLMs Keep Thinking When Told Not To ▲241
- Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence ▲224
- Questioning the Questions: Sustaining Self-Evolution in Reasoning Models ▲85
- Improving Test-Time Scaling with Adaptive Looped Transformers ▲62
- Hybrid Reasoning Agents ▲38
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-22。
要点由本站根据摘要自写，不转载摘要原文，请阅读原文。