Hacker Times

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Critic Questions How Astra Weight-Editing Experiments Were Presented

A November 3 critique argues that the reported Qwen math gains relied on Python code and repeated model runs, unlike raw-weight-only tests on much smaller networks. It credits the engineering result while disputing the implication that a single technique explains all the experiments.

Researchers Report Direct Edits to Neural-Network Weights

An MIT CSAIL team reports that Astra improved Qwen’s math scores by editing weights using Python and feedback from practice runs. In the test allowing 50 forward passes, the authors report MATH-500 rising from 7.9% to 48.1%. These preliminary results are separate from the team’s raw-weight-only experiments on smaller networks.

The authors’ diagram of experiments reading, repairing and improving neural-network weights
Rikiya Takehi and colleagues / MIT CSAIL

Anthropic S-1

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Illustration via WIRED

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