(Mis)generalization of Helpful-Only Fine-tuning

·LessWrong··

TLDRWe study the shortcomings of existing helpful-only models. We find that some show emergent misalignment, others have residual refusal behaviors, and most show poor steerability, sycophancy, and incoherent character. None of these problems are a necessary consequence of helpful-only training, though: we show that synthetic document fine-tuning and adding character-related questions to SFT and RL can mitigate them.Research done as part of MATS/Anthropic Fellows Program. See here for the full p...

Read full article →

Related Articles

New HIV vaccine shows unprecedented success in preclinical study
codebyaditya · Hacker News · 6h ago
A walk through of the DeltaNet family of linear attention variants
AnhTho_FR · Hacker News · 3h ago
GrapheneOS Defends Data-Wiping Function That Blocked US Border Search
pseudolus · Hacker News · 4h ago
US citizen charged after GrapheneOS phone wipes during airport search
eecc · Hacker News · 1d ago
Zig's Incremental Compilation Internals
garyhtou · Hacker News · 4h ago