谷歌 DeepMind 推新框架 InfAlign：提升语言模型推理对齐能力
生成式语言模型在从训练到实际应用的过程中面临着许多挑战。其中一个主要问题是如何在推理阶段使模型达到最佳表现。目前的对策，如通过人类反馈的强化学习（RLHF），主要集中在提高模型的胜率上，但往往忽视了推理时的解码策略，例如 Best-of-N 采样和控制解码。这种训练目标与实际使用之间的差距，可能导致效率低下，影响输出的质量和可靠性。为了解决这些问题，谷歌 DeepMind 和谷歌研究团队开发了 InfAlign，这是一个旨在与推理策略相结合的机器学习框架。InfAlign 将推理时的方法
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