伯克利联手Alec Radford发布GLP：用扩散模型重构LLM激活值，突破可解释性瓶颈
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伯克利联手Alec Radford发布GLP：用扩散模型重构LLM激活值，突破可解释性瓶颈
伯克利联手Alec Radford发布GLP：用扩散模型重构LLM激活值，突破可解释性瓶颈 这项研究介绍了一种名为生成潜先验 (GLP) 的创新架构，通过在十亿级规模的 LLM 激活值上训练扩散模型，构建出能够理解神经网络内部状态分布的“元模型”。GLP ...
5 days ago
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