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Retrieval methods can be dramatically improved by tailoring them to specific ideation operations, as shown by RATIO's performance enhancements.
Rationale supervision can boost performance on complex scientific problems but may backfire on simpler ones, revealing critical insights into AI training dynamics.
Achieving unprecedented consistency in cross-representation learning, CoCoEvolve outperforms existing methods by leveraging one-to-one correspondences without extra annotations.
