MIT Paper: LLMs Natively Read and Write NN Weights, Lifting Qwen MATH-500 from 7.9% to 48.1%
ivan_bezdomny · x · 2026-11-03
MIT CSAIL researchers (Takehi, Teoh, Zhang, Khattab) show frontier LLMs can natively read/write neural network weights. GPT-6 Astra identifies a network's training game from raw weights alone, writes game-playing nets beating PPO-trained ones, and fixes Qwen3.5-0.8B's reasoning loops by editing 0.016% of weights — raising MATH-500 from 7.9% to 48.1% and IFEval 3x, with no gradients or training loops. They call it Weight-Space Programming.
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