MIT CSAIL proposes weight space programming: GPT-6 Astra modifies Qwen3.5-0.8B's weights by about 0.016%, boosting MATH-500 score to 6 times
MIT CSAIL researchers propose 'weight space programming', allowing GPT-6 Astra to directly read and modify the neural network weights of Qwen3.5-0.8B, adjusting only about 0.016% (131072 parameters) to increase MATH-500 score from 7.9% to 48.1%, GSM8K from 13.8% to 67.1%, and IFEval from 21.0% to 62.3%.
Same story — featured version shown《MIT experiment: GPT-6 Astra directly modifies Qwen3.5 weights, mathematical ability improves by about 6 times》
Same story3 other outlets also reported this
- Hacker News · 300+··First
Astra can read and write neural network weights and improve Qwen3.5-0.8B
- QbitAI··+7 h 36 min
MIT experiment: GPT-6 Astra directly modifies Qwen3.5 weights, mathematical ability improves by about 6 times
Adds:MATH-500 score improvement from 7.9% to 48.1%.
- ITHome · AI··+7 h 39 min·Reading now
MIT CSAIL proposes weight space programming: GPT-6 Astra modifies Qwen3.5-0.8B's weights by about 0.016%, boosting MATH-500 score to 6 times
Adds:GSM8K score improvement from 13.8% to 67.1% and IFEval score improvement from 21.0% to 62.3%.
- Latent Space··+2 d
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Source: ITHome · AI · ithome.com