Weight Space Programming lets LLMs read and edit neural network weights
Direct weight editing by LLMs reframes model debugging: instead of retraining, practitioners could patch specific failure modes like repetitive outputs in place. The GDPx benchmark and DeepSeek super-agent references suggest early infrastructure is forming around this idea. Researchers and engineers working on post-training or model introspection should track how these methods compare with fine-tuning workflows.
