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Sewer-Transformer-ML is developed, a hierarchical vision Transformer with multi-level feature fusion together with two lightweight architectures, Sewer-MobileNet-ML and Sewer-Mobile-TransNet, for resource-constrained inspection scenarios and provides a computational basis for automated sewer inspection, lightweight model design, and adaptation across civil infrastructure inspection platforms.
AdaptRubric's innovative two-stage framework boosts GUI reward modeling performance by over 3.6 F1 points, showcasing the power of task-adaptive criteria.
Real-time semantic corrections during video generation can drastically enhance visual fidelity and coherence without retraining the model.
