arXiv 2610.17309 · cs.CL · 2026-10-12
StartLux-Decision: AutoThink Decision Models with Reinforcement Learning for Calibrated Deliberative Decisions
Xialie Zhuang, Zunhai Su, Jia Pan, Ngai Wong, Guanhua Chen, Chuan-Wei Kuo
StartLux
在最新榜 #211 本站收录于 2026-10-22
一句话要点
StartLux-Decision 决策模型（0.8B–27B）对有把握的情况直接作答、不确定时才推理，并用强化学习校准决策概率。
StartLux-Decision models (0.8B–27B) answer confident cases directly and reason only when uncertain, with RL that rewards calibrated decision probabilities.
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主题与学科
同主题：推理
- LEV: Thinking Fast and Deep with Looped Decision Models ▲602
- 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
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。