LLMs Think in Geometry Across Languages
💡LLMs encode concepts geometrically across langs/code/math in 4 models—universal rep breakthrough
⚡ 30-Second TL;DR
What Changed
Tested 8 languages (EN, ZH, AR, RU, JA, KO, HI, FR) on Qwen3.5-27B, MiniMax M2.5, GLM-4.7, GPT-OSS-120B
Why It Matters
Challenges Sapir-Whorf hypothesis; supports Chomsky-like universal structures but geometric. Enables better interpretability and cross-lingual transfer.
What To Do Next
Interact with PCA visualizations at https://dnhkng.github.io/posts/sapir-whorf/
Key Points
- •Tested 8 languages (EN, ZH, AR, RU, JA, KO, HI, FR) on Qwen3.5-27B, MiniMax M2.5, GLM-4.7, GPT-OSS-120B
- •Middle layers show language identity vanishes; concepts cluster semantically
- •Modality-agnostic: ½mv², Python '0.5 * m * v ** 2', English description converge
- •Replicates in dense transformers and MoE architectures
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Original source: Reddit r/LocalLLaMA ↗
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