本期《TAI快报》深入探讨了AI领域的五项前沿研究，涵盖优化算法、强化学习、学术工具、脑启发计算和偏好学习。具体内容包括： 《In Search of Adam's Secret Sauce》揭示了Adam优化器的成功秘诀在于自适应调整，通过简化参数（β1=β2）仍保持近最优性能，并提供全新理论解释。 《Diffusion Guidance Is a Controllable Policy Improvement Operator》提出了CFGRL框架，结合生成模型与强化学习，通过可控引导提升策略表现。 《Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers》推出了PosterAgent系统，低成本高效生成学术海报，为科研交流提供新工具。 《Self-orthogonalizing Attractor Neural Networks Emerging from the Free Energy Principle》从自由能原理推导出自组织神经网络，展现正交表征和序列学习能力。 《Understanding the Performance Gap in Preference Learning: A Dichotomy of RLHF and DPO》理论分析了RLHF与DPO的性能差异，为AI对齐人类偏好提供指导。完整推介：https://mp.weixin.qq.com/s/V57mRouVSAHXEy5NY22P9g
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