AI前沿：AI如何学会更高效地思考和行动

本期“TAI快报”深入探讨五项AI前沿研究： “ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning”提出强化学习方法优化语言模型推理长度，显著提升效率，推理长度减半性能仅降2%。 “Critical Thinking: Which Kinds of Complexity Govern Optimal Reasoning Length?”揭示任务顺序复杂度决定AI最佳推理长度，提出预测“黄金长度”提升准确率。 “Sparse Gaussian Neural Processes”融合高斯过程可解释性和神经过程高性能，实现在小样本场景下快速、可靠预测。 “Prompting Forgetting: Unlearning in GANs via Textual Guidance”创新性地用文本提示让生成模型“遗忘”特定内容，保护隐私与安全。 “Review, Refine, Repeat: Understanding Iterative Decoding of AI Agents with Dynamic Evaluation and Selection”通过迭代优化提升AI智能体复杂任务性能，验证器反馈是关键。完整推介：https://mp.weixin.qq.com/s/eyj2QslilVIb1OuIdRn6cg

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