4 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 4 cited
Opening the AI black box: program synthesis via mechanistic interpretability
Eric J. Michaud, Isaac Liao, Vedang Lad +7
We present MIPS, a novel method for program synthesis based on automated mechanistic interpretability of neural networks trained to perform the desired task, auto-distilling the le…
cs.LG2024★ 2 cited
Universal Neurons in GPT2 Language Models
Wes Gurnee, Theo Horsley, Zifan Carl Guo +5
A basic question within the emerging field of mechanistic interpretability is the degree to which neural networks learn the same underlying mechanisms. In other words, are neural m…