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This paper introduces CW-BASS v2, a saturation-aware pseudo-label selection method for semi-supervised semantic segmentation that adaptively switches between strict filtering and an adaptive confidence floor depending on the teacher's reliability. It shows improved results over baselines across several benchmarks with DINOv2 teachers.