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Superficial reasoning in video temporal grounding can be transformed into high-quality, time-aware insights with the right optimization framework.
Reconstructing high-fidelity 3D heart models from noisy radar data is now possible, thanks to a novel mesh deformation approach that leverages physics-informed learning.
MLLMs are better at understanding videos than directly grounding text queries within them, and a self-correction training loop can close the gap.
