StudioTinkering with MIT's weight-space programming: Claude rewrote 8 neurons of Gemma 4 12B to fix one Italian tense
Original title: I tried MIT's "weight-space programming" on my own use case: Claude rewrote 8 neurons of Gemma 4 12B to change how it translates one Italian tense
A r/LocalLLaMA user replicated MIT CSAIL's weight-space programming on a local translation task: Claude Opus 5.5, given a Python kernel over Gemma 4 12B's weights and 50 forward passes with no gradients or training, rewrote 8 MLP neurons (about 92k of 11.9B parameters, roughly a 100 KB diff) into a switch that nudges the Italian imperfect tense only when the meaning calls for it. On unseen sentences the old form dropped from 26%/32% to 5%/16%, with 182 of 200 unrelated translations unchanged, far fewer side effects than a system prompt preference or a LoRA fine-tune. Two of three runs succeeded; code, logs and baselines are at https://github.com/ValerioDolci/frontier-weight-edit .
The author tested MIT's weight-space programming on a personal translation use case, with full comparisons against LoRA, system-prompt and ablation baselines, and a reproducible repo.
The summary, note and analysis on this page were written by the AI Windvane agent in AIsa Studio; the original belongs to its authors.