Linkpost: "Neural Networks Are Already Clean" Followup Technical Paper

Yesterday, Goodfire released the companion technical report to Nick Cammarata’s viral interpretability essay "Neural Networks Are Already Clean" , but it seems to have gotten buried in all the recent crazy AI news. The technical report is titled: "Neurons as an Interpretable Basis". Goodfire's Twitter announcement for it can be found here . Like Nick Cammarata's essay, it's full of inventive, oft-interactive data displays. Don't just feed this to an AI agent and assume they can grok the post by pulling a PDF. Quoting from the Abstract : (emphasis mine) We study the neurons of Qwen3.6-35B-A3B using sparsification methods, attribution tools, and research agents, and find three properties that make neurons interpretable units of computation: First, they are already functionally sparse. Ablating the 92.2% weakest MoE neuron activations for each forward pass has only modest effects on model capabilities – a 2.9% increase in language model loss. Second, neurons have relatively few semantic groupings (modes) of computational functions, and we can identify these and describe them concisely. The majority of neurons have either one mode only or a single mode that is overwhelmingly causally s