DART uses ambiguity steering vectors to curb LLM overconfidence

Researchers propose DART, which builds ambiguity steering vectors via interpretability techniques to guide fine-tuning, reducing overconfidence across seven LLMs even when they don't know the answer.

2026-11-10 ~ 2026-11-11 · 2 related posts

• DART: interpretability-guided fine-tuning fixes LLM overconfidence across 7 models — MaartenSap · 2026-11-10

1 near-duplicate retellings: dhadfieldmenell