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介绍了五项AI研究:1. 多元化奖励的CFG蒸馏,在不增加计算成本的前提下,提高AI生成内容的多样性和质量;2. 上下文强化学习,探索大型语言模型通过奖励信号自我优化学习新任务;3. 揭示了自动化评测大型语言模型的漏洞,即“空模型”也能获得高分;4. 发现重复训练少量样本可以提升模型在特定任务上的表现;5. 提出了一种新的采样算法——噪声校正朗格文算法,能够更高效地从无噪声分布中采样。完整推介:https://mp.weixin.qq.com/s/fzD99zz8BICTRrVPN9oMxg
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