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EurekaBench is introduced, a cross-domain benchmark that tests AI agents'ability to conduct long-horizon experiments and discover mechanisms that explain observations, and shows that current AI agents often overly fixate on predictive accuracy optimization, surpassing human scientists, while falling substantially short...
This suite provides a new efficient lens on generalization: select intermediate pre-training checkpoints that strongly generalize reasoning and alignment, better than the final pre- or mid-training checkpoints, and select pre-training data that controls and stabilizes generalization dynamics.
This work introduces PRISM Edit, which optimizes a single polysemous representation across temporal contexts and leverages the model's inherent modulation pathway to route it to temporally correct predictions without requiring any architectural modification.
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