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SKILLER achieves up to 20.4 percentage points improvement in skill generation for small language models, making high-quality task execution accessible without the prohibitive costs of closed-source solutions.
Multi-agent systems get a 6.3% accuracy boost on math problems thanks to a new "rectify-or-reject" pruning method that dynamically filters out bad information at test time.
