Reasoning and learning about injected concepts in language models

This work was done as a part of SPAR, under the mentorship of Mirko Bronzi and Damiano Fornasiere. TL;DRWe test models' ability to recover information about their activations by injecting steering vectors, and asking the LLMs to verbalize properties of them. We train models with in-context learning and test for three capabilities: Can models identify the region of layers (early, middle, late) of the injection?Can models identify the relative magnitude (low, medium, high) of the injection?Can mod...