We propose CARML, a novel retrieval-augmented editing framework that integrates conflict-aware dynamic retrieval with multi-level collaborative guidance for reliable lifelong multimodal editing.

RL to train LLMs how to generate data and update themselves to adapt to new knowledge/tasks.

NMKE is a fine-grained framework that uses neuron-level attribution and sparse masking for precise, efficient lifelong knowledge editing.