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Unified benchmarks reveal the state-of-the-art in simultaneously addressing multiple real-world image degradations like blur, low-light, and rain.
Saliency detection in remote sensing gets a huge speed boost with ORSIFlow, a rectified flow approach that leaps ahead of slower diffusion-based methods.
Geometric mappings can dramatically improve PINN training, boosting accuracy and stability by aligning input coordinates with the underlying physics of PDEs.
Topological data analysis reveals that structurally stable and compact soft prompts lead to better downstream performance, enabling a new loss function (TSLoss) that improves convergence and tuning performance.