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📽️ New NVIDIA paper: Motion Attribution for Video Generation 📽️
We propose MOTIVE, a method for taking query video clips and identifying which training data will improve or degrade performance after finetuning, enabling sophisticated data curation and beyond!
🔎 Project Page: https://research.nvidia.com/labs/sil/projects/MOTIVE/
📖 Full Paper: https://arxiv.org/abs/2601.08828
Check out more work from the NVIDIA Spatial Intelligence Lab here: https://research.nvidia.com/labs/sil/
This project was led by the great work of Xindi(Cindy) Wu, along with Despoina Paschalidou, Jun Gao, Antonio Torralba, Laura Leal-Taixé, Olga Russakovsky, and Sanja Fidler.
We propose MOTIVE, a method for taking query video clips and identifying which training data will improve or degrade performance after finetuning, enabling sophisticated data curation and beyond!
🔎 Project Page: https://research.nvidia.com/labs/sil/projects/MOTIVE/
📖 Full Paper: https://arxiv.org/abs/2601.08828
Check out more work from the NVIDIA Spatial Intelligence Lab here: https://research.nvidia.com/labs/sil/
This project was led by the great work of Xindi(Cindy) Wu, along with Despoina Paschalidou, Jun Gao, Antonio Torralba, Laura Leal-Taixé, Olga Russakovsky, and Sanja Fidler.
