Editing 0.016% of weights fixes Qwen reasoning loops, lifting MATH-500 to 48.1%
A researcher used Jacobian lens interpretability tools to study Qwen3.5-0.8B's 'Wait' reasoning loops, replicating MIT CSAIL's weight-editing fix. Editing about 131k weights (0.016%) across two MLP layers lifted MATH-500 accuracy from 7.9% to 48.1%.
2026-11-03 ~ 2026-11-03 · 2 related posts
- Episode 1: MIT's Weight-Space Programming: GPT-6 Edits Neural Weights Directly(2026-11-03, 92 posts)
- Episode 2: LLMs Editing Model Weights: From Survey to Self-Editing Experiments(2026-11-03, 5 posts)
- Episode 3: Editing 0.016% of weights fixes Qwen reasoning loops, lifting MATH-500 to 48.1%(2026-11-03, 2 posts)
- Episode 4: Model eval audit continues: claimed gains hold but MATH-500 anomaly persists(2026-11-03, 3 posts)
- Episode 5: MIT weight-space programming independently replicated, with 20x gains on newest models(2026-11-03, 7 posts)
- Episode 6: Weight-Editing LLMs Raise Fear of Recursive Self-Improvement(2026-11-03, 3 posts)
- Editing 131k weights to fix looping: activation steering yields free benchmark gains — xennygrimmato_ · 2026-11-03
- Editing 0.016% of weights fixes Qwen reasoning loops, MATH-500 jumps from 7.9% to 48.1% — DeliciousGorilla · 2026-11-03