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SCRIBE uses an ensemble of open-source large models to generate interpretable word-level semantic representations, and validated at both the behavioral experiment and brain imaging levels the consistency of these representations with human semantic judgments and brain activity.
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10/16/2026
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UnverifiedSCRIBE's methodological path—using large models to generate interpretable intermediate representations and then using neural data to verify their alignment with brain computation—can be transferred to other cognitive domains.78% similarUnverifiedVariance decomposition analysis showed that SCRIBE still explained unique brain-predictive information beyond the syntactic features selected by the researchers.77% similarUnverifiedThis study is the first to use an interpretable semantic framework to quantify how much of brain-LLM alignment comes from comprehensible semantics.71% similarUnverifiedThe combination of behavioral and imaging methods is one of the standard paradigms in current neuroscience experiments.70% similarUnverified稀疏自编码器(SAE)将模型激活分解为人类可解释的特征方向，Anthropic的Claude系列模型可解释性研究大量使用了这一技术70% similar
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