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School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
CMU Machine Learning2
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5
Nine out of ten AI-selected modeling changes in materials science remain effective when tested on unseen data, showcasing the potential for reusable AI-driven discoveries.
Continual learning for LLM agents hits a wall: scaling models doesn't reliably improve skill generation, and self-feedback can lead to recursive drift.
