In-Context Learning for Pure Exploration

Researchers introduce In-Context Pure Explorer (ICPE), a Transformer-based model that learns to actively collect data and identify correct hypotheses in sequential testing problems without parameter updates. The model demonstrates competitive performance across various benchmarks including multi-armed bandit problems and generalized search tasks.