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The toolkit provides a complete pipeline: from probing a model's hidden states to locate refusal directions, through multiple extraction strategies (PCA, mean-difference, sparse autoencoder decomposition, and whitened SVD), to the actual intervention — zeroing out or steering away from those directions at inference time. Every step is observable. You can visualize where refusal lives across layers, measure how entangled it is with general capabilities, and quantify the tradeoff between compliance and coherence before committing to any modification.
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Moongate loads gameplay templates from DirectoriesConfig[DirectoryType.Templates]:
This is effectively what ray-marching does and is pretty much the bread and butter of modern volume rendering. It’s extremely flexible – we don’t care what the density function is, and in fact we may not even know what it is, but as long as we can sample it at arbitrary points (e.g. via a volume texture) we can numerically evaluate the integral.,推荐阅读体育直播获取更多信息
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