We removed an LM's ability to speak German (3 minute read)

TLDR AI Papers
interpretability neural-geometry language-model control debugging research-agenda

Summary

GoodfireAI releases a research agenda on understanding neural geometry in language models, demonstrating the ability to precisely control a model's capabilities, such as removing its ability to speak German.

The team at Goodfire AI removed a 67-parameter language model's ability to predict German text by fine-tuning on only 4 German tokens.
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Cached at: 06/26/26, 05:10 PM

# Thread by @GoodfireAI on Thread Reader App Source: [https://threadreaderapp.com/thread/2070181051801235463.html](https://threadreaderapp.com/thread/2070181051801235463.html) Neural networks might speak English, but they think in shapes\. Understanding their rich \*neural geometry\* is key to understanding how they work – and to debugging and controlling them with precision\. Starting today, we’re releasing a series of posts on this research agenda\. 🧵 ![Video Poster](https://pbs.twimg.com/amplify_video_thumb/2052420395459067904/img/Qw46DHLl_4uBne5w.jpg) Just as the real world is highly structured, neural networks are full of rich geometric structure: time, space, numbers, color, the tree of life, new biomarkers, and more are represented along curved paths and surfaces\. This is true across models, modalities, and domains\! \(2/8\) New methods to understand this “neural geometry” are a crucial frontier in understanding, improving, and controlling models\. \(3/8\)

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