Automated Researchers Can Reliably Mitigate Alignment Failures
Fine tuning aligned language models compromises safety, even when users do not intend to
2024
2025
Narrow fine-tuning changes the model's latent hypothesis / world-model itself, resulting in fundamental behavioral changes such as text style shifts, era/identity switches, and context/factual framework transitions. Focus on the generalization pattern where misaligned behavior extends to broad contexts.

Seonglae Cho