Introspection Fine-Tuning (IFT): Training Small LLMs to Detect and Report Internal Changes
Researchers introduce Introspection Fine-Tuning (IFT), a method that trains small language models to detect and report perturbations in their own internal activations. This breakthrough could make AI systems more reliable and transparent by enabling self-monitoring in smaller, efficient models.
