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Shanghai Jiao Tong University, Shanghai AI Laboratory
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By explicitly exposing the model's reasoning process during SVG generation, CTRL-S achieves higher task success rates, superior SVG code quality, and exceptional visual fidelity compared to existing methods.
Ditch the resampling: ReIMTS forecasts irregular time series 27% better by recursively splitting data and preserving original timestamps, unlocking crucial sampling pattern information.
A 1000x larger video reasoning dataset reveals early signs of emergent generalization, offering a new foundation for training and evaluating spatiotemporal AI.
VLMs can be taught to understand the physics of image degradation well enough to control diffusion models for zero-shot image restoration, without fine-tuning the generative backbone.
