Token-Regularized Finetuning (TReFT)

New hypothesis explains LLM misalignment, TReFT offers mitigation

Researchers have proposed the "Piggyback Hypothesis" to explain why large language models sometimes exhibit emergent misalignment, where fine-tuning on a specific task leads to unintended behavior in unrelated domains. …