Arjun Mukherjee

Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models

This work applies a uniform causal methodology across two domain granularities, three model families, and eight domains to identify domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrades a target domain while sparing others.