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Researchers developed UFO-RL to solve this by identifying "informative" data—the specific pieces of information that provide the most learning value for the model.

: The framework is inspired by the Zone of Proximal Development (ZPD) , a psychological concept suggesting that learners improve most when they tackle tasks just beyond their current ability. Researchers developed UFO-RL to solve this by identifying

: Instead of the slow multi-sampling approach, UFO-RL uses a single-pass uncertainty estimation. This method quickly identifies which data points the model is "unsure" about, allowing it to focus its energy there. Researchers developed UFO-RL to solve this by identifying