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This paper introduces CUSP, a benchmark for evaluating AI systems' ability to forecast scientific progress, finding that current models show systematic overconfidence and domain-dependent limitations, failing to reliably predict scientific advances.
OpenAI introduces a method for learning complex nonlinear system dynamics using deep generative models over temporal segments, enabling stable long-horizon predictions and differentiable trajectory optimization for model-based control.