SafeEdit encompasses 4,050 training, 2,700 validation, and 1,350 test instances. SafeEdit can be utilized across a range of methods, from supervised fine-tuning to reinforcement learning that demands preference data for more secure responses, as well as knowledge editing methods that require a diversity of evaluation texts.
