Context Confusion

A risk phenomenon in the post-training stage of large language models in which, even when training samples are fully aligned, similar representational shifts across different domain queries during fine-tuning can cause aligned behaviors to be incorrectly transferred to semantically adjacent contexts, inducing narrow misalignment.