VAnim creates open-domain text-to-SVG animations via sparse state updates on a persistent DOM tree, identification-first planning, and rendering-aware RL with a new 134k-example benchmark.
International Conference on Learning Representations (ICLR) , year=
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ECTraj enhances consistency models for multi-agent trajectory prediction via improved student-teacher supervision and conditional top-K generation, yielding faster inference and competitive accuracy on Argoverse 2.
Pairing regularization mitigates intra-mode collapse in GANs by penalizing redundant latent-to-sample mappings, improving recall under collapse-prone conditions or precision under stabilized training.
citing papers explorer
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VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation
VAnim creates open-domain text-to-SVG animations via sparse state updates on a persistent DOM tree, identification-first planning, and rendering-aware RL with a new 134k-example benchmark.
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Enhancing Consistency Models for Multi-Agent Trajectory Prediction
ECTraj enhances consistency models for multi-agent trajectory prediction via improved student-teacher supervision and conditional top-K generation, yielding faster inference and competitive accuracy on Argoverse 2.
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Pairing Regularization for Mitigating Many-to-One Collapse in GANs
Pairing regularization mitigates intra-mode collapse in GANs by penalizing redundant latent-to-sample mappings, improving recall under collapse-prone conditions or precision under stabilized training.