Article by Shenchao TechFlowNo training required, no data needed, no gradient descent.Researchers at MIT fed the weights of ...
The complete logs of every experiment in the blog post Sparks of Weight Space Programming: LLMs can understand and write neural network weights. For each experiment you get: everything we sent the ...
A new MIT CSAIL blog post is making the rounds in AI circles this week, and it describes something that sounds almost ...
In the strongest example of "weight space programming", as the technique is called, Astra’s intervention raised Qwen3.5-0.8B’s MATH-500 score from 7.9% to 48.1% while touching approximately 0.016% of ...
MIT CSAIL researchers say GPT-6 Astra edited 0.016% of Qwen3.5-0.8B weights to fix reasoning loops, lifting MATH-500 from 7.9% to 48.1% without training.
Astra identifies game policies from raw weight matrices and fixes reasoning loops in Qwen3.5-0.8B by editing 0.016% of parameters, lifting MATH-500 scores from 7.9% to 48.1% without training loops.
Python libraries that replace hundreds of lines of custom code. LiteLLM, Instructor, Tenacity, and 5 more I use in every ...
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