Decodable but not detachable: training data granularity determines parametric modularity in large language models
Read the original at arxiv.org→arXiv:2608.10214v1 Announce Type: new Abstract: Do large language models contain domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrades a target...
Original headline: "Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models"
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- Aug 12, 04:00 UTC arXiv cs.AI lead source Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models