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Natural paper revisions can be harnessed to train AI agents for precise and context-aware editing of complex scientific diagrams.
Transforming multimodal resources into executable agent skills boosts performance by nearly 12 percentage points, showcasing the power of diverse learning materials.
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.
Synthetic motion data, when represented as optical flow, unlocks a new level of realism and control in video diffusion models, surpassing the limitations of real-world datasets.
