MIT researchers use GPT-6 Astra to directly edit Qwen3.5-0.8B weights, lifting math scores
Researchers report GPT-6 Astra edited 0.016% of Qwen3.5-0.8B's weights without gradient-based training, raising its MATH-500 score from 7.9% to 48.1% and fixing reasoning loops.
Read the full story at Techmeme ↗
Timeline · 8 reports
- 2026-11-03 14:30 · DEV Community — Machine Learning
GPT-6 Astra Edited Qwen3.5-0.8B's Weights. The MATH-500 Jump Was a Loop Fix - 2026-11-03 14:16 · DEV Community — Machine Learning
Hydrogen-1.0 MIT Open Weights: Gated BF16, NVFP4 262K Context Cliff, and Vendor FSR vs GPT-6 Astra - 2026-11-02 22:16 · VentureBeat AI
'Like gene editing for neural networks': MIT researchers used GPT-6 Astra to edit Qwen's open weights directly, boosting math performance - 2026-11-02 21:36 · r/LocalLLM
MIT researchers say GPT-6 Astra improved a small Qwen model’s math score from 7.9% to 48.1% by directly editing just 0.016% of its weights, without gradient-based training. - 2026-11-02 21:25 · r/LocalLLaMA
GPT-6 Astra Edits Qwen Weights: MATH-500 7.9% to 48.1% - 2026-11-02 21:00 · Ethan Mollick (X)
If this holds up, it is big: "We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math - 2026-11-02 20:18 · r/singularity
MIT researchers say GPT-6 Astra improved a small Qwen model’s math score from 7.9% to 48.1% by directly editing just 0.016% of its weights, without gradient-based training. - 2026-11-02 20:00 · Techmeme
Researchers say LLMs can be good at natively reading and writing neural network weights; GPT-6 Astra edited Qwen3.5-0.8B's weights to make it better at math (Rikiya Takehi)