Weight editing can fix LLM reasoning flaws but can't improve reasoning itself
1a3orn · x · 2026-11-03
A follow-up observation on the Weight-Space Programming experiment: if there's a clear flaw in an LLM's reasoning, LLMs can help edit it out — but they don't seem to improve reasoning even for very small LLMs, on a very small toy domain.
A key caveat: the technique works more like bug-fixing by elimination than general capability enhancement.
Related event: LLM Weight Edits Fix Flaws But Fail to Boost Reasoning, Researcher Finds(2 posts)→
More from Research
- New Kaggle benchmark transcribes 1621–1737 Portuguese records; Gemini 4 Argon leads at 0.86 — mariofilhoml · 2026-11-03
- Latent Space pod: MIT's Alex Zhang on RLMs, agent swarms and OpenAI's 10,000-agent experiment — niloofar_mire · 2026-11-03
- LeVJEPA 1.5 Large matches V-JEPA with 5.6x less compute and 10x less data — HildeKuehne · 2026-11-03
- Prime Intellect resident poses the RL frontier problem: how do you reward unverifiable knowledge work? — xeophon · 2026-11-03
- Yoav Goldberg speculates RL training included tasks on interpreting and editing model weights — yoavgo · 2026-11-03
- Understanding AI deep dive: reinforcement learning with minimum math made agents like o3 possible — binarybits · 2026-11-03