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Results show that distinguishing structural details from degradation-induced interference is more effective for underwater segmentation, and GeoCueFormer achieves SOTA performance while maintaining a favorable accuracy-complexity trade-off.
TSRCA-PPO slashes control errors and energy consumption for ROVs, outperforming traditional methods by up to 93.5% in key metrics.
Tail classes in medical image classification can be effectively shielded from head-class encroachment, leading to significant improvements in performance.
Steering signals are most effective when derived from execution-boundary states, not just from the presence of desired behaviors in the source text.
