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Forget blindly chasing teacher-student disagreement in on-policy distillation – focusing on *learnable* disagreement, where the teacher nudges the student within its existing possibilities, unlocks surprisingly efficient learning.
Model-generated skills can actually hurt agent performance, and bigger models don't necessarily make for better skill extractors or consumers.
SkillOpt transforms agent skill development into a reproducible optimization process, achieving state-of-the-art results by treating skills as trainable parameters.
Hierarchical planning and self-reflection can finally wrangle AIGC tools into producing coherent, visually consistent webpages.
Today's best text-to-audio-video models may look and sound impressive, but they still struggle with basic physics, coherent speech, and even rendering text correctly.
Current image generation models fall far short of the mark when it comes to the structured and multi-constraint demands of real-world commercial design, as revealed by a new systematic benchmark.
