AI
Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights
Publication: top scoring links : multi
Author: /u/Pyros-SD-Models
Source published: 02/11/2026, 18:45:06 UTC
Briefing created: 03/11/2026, 03:14:30 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 03/11/2026, 01:48:25 UTC.
Briefings
A user named Astra successfully edited Qwen3.5-0.8B weights to improve math reasoning and instruction following without training. The edit involved only 0.016% of the weights, resulting in up to 6x improvement in math and 3x in instruction following. This capability represents a significant step toward self-editing models.
Key points
- Astra edited Qwen3.5-0.8B weights to improve math reasoning and instruction following without training.
- The edit involved only 0.016% of the weights, resulting in up to 6x improvement in math and 3x in instruction following.
Context
This finding demonstrates that LLMs can natively read and write neural network weights, a capability previously thought to require training. The evidence comes from a user named Astra who directly changed only 0.016% of weights to improve performance.
Limitations
The evidence is limited to a single user report from a Reddit thread. No independent verification, controlled experiments, or peer-reviewed validation of the results are provided in the source.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 03/11/2026, 03:14:30 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
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