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全注意力、复杂推理不掉速:MiniMax M2把Agent做成了「可执行能力」
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Open-weight training practices and implications for CoT monitorability
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Advancing Explainable AI in Radiology Research with NVIDIA Clara Reason
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让机器人「不仅会想,还能准确去做」,VLA-R1把「推理+行动」带进真实世界
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让机器人「不仅会想,还能准确去做」,VLA-R1把「推理+行动」带进真实世界
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Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability
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Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability
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Highlights from Explaining AI Explainability
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Highlights from Explaining AI Explainability
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A Concrete Roadmap towards Safety Cases based on Chain-of-Thought Monitoring
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SDC2025 精彩议题预告 | SCPGA:自认同CoT渐进式泛化攻击
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First Try Matters,不是Aha Moment:邴立东团队揭示推理模型靠首答,不靠反思
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AI-202X-slowdown: can CoT-based AIs become capable of aligning the ASI?
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AI-202X-slowdown: can CoT-based AIs become capable of aligning the ASI?
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NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining
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NVIDIA Researchers Propose Reinforcement Learning Pretraining (RLP): Reinforcement as a Pretraining Objective for Building Reasoning During Pretraining
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CoT 之后,CoF 如何让帧间逻辑从「隐式对齐」变成「显式思考」?
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