Activation-Based Active Learning for In-Context Sample Selection

arXiv 2606.05134·medium signal

Osman, Merrett, and Middleton apply activation-based active learning to choose in-context examples for LLMs, going beyond prior deep active learning approaches that didn't leverage model internals. The goal is picking the most informative ICL demonstrations to lift performance. Relevant for prompt engineers optimizing few-shot example selection.