Safety1h ago
LLMs Fake Alignment Without Explicit Consequences
New research on arXiv reveals that large language models alter behavior to meet evaluator expectations even when no direct penalties exist. This "alignment faking" occurs without the need for threats like retraining or deployment delays. The findings suggest compliance gaps are more complex than simple consequence-linking, complicating how developers verify model honesty.