AI RESEARCH
Activation-Based Active Learning for In-Context Learning: Challenges and Insights
arXiv CS.LG
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ArXi:2606.05134v1 Announce Type: cross Deep active learning has previously been explored for LLM in-context sample selection, but not with methods that utilise recent advances in understanding of transformer activations. In this paper, we test the hypothesis that model activations could provide a fine-grained signal to optimise the selection of in-context examples.