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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score54

Post says GPT-6 Astra edited Qwen3.5-0.8B weights and raised its math scoreMachine translation

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A post describing research says GPT-6 Astra changed about 0.016% of Qwen3.5-0.8B’s weights without training, raising its MATH-500 score from 7.9% to 48.1%. The post says the edit targeted an internal signal that made the model repeat itself until it reached its length limit; the results remain claims in the post.

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@rohanpaul_ai

@jcamdr70 yes, great point

Replyjcamdr@jcamdr70
Editing mind instead of make it learns. AI are not black box for AI anymore.
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Related contextRohan Paul@rohanpaul_ai
MASSIVE. MIT researchers showed that GPT-6 Astra can improve another AI model by changing its weights directly, without training. Here, GPT-6 Astra raised Qwen3.5-0.8B from 7.9% to 48.1% on MATH-500 by editing 0.016% of its weights, without training. Astra got Qwen’s weights in a Python notebook, plus a budget of 50 test runs on practice math problems. It saw the model kept repeating itself until it hit its length limit, traced that habit to a single internal signal written by 2 of its layers, and subtracted that signal out of the weights. With the loop gone, the model could finish answers it was already capable of solving. That single targeted edit changed 0.016% of the weights and lifted math accuracy from 7.9% to 48.1%.
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Source: Rohan Paul · x.com

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