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The paper introduces a weakly supervised multi-label proportion learning framework for sea-ice type prediction using SAR imagery and multimodal data, achieving significant accuracy improvements over supervised baselines.
This paper investigates weakly-supervised ByT5 fine-tuning for stress-aware sentence-level Filipino grapheme-to-phoneme conversion, achieving significant improvements in phoneme and character error rates on a manually-corrected test set.
SUFLECA is a weakly-supervised framework for zero-shot CAD-to-image alignment, achieving state-of-the-art accuracy on ScanNet25k by scaling up geometry-grounded feature learning from pretrained visual representations.
GUICrafter introduces a weakly-supervised GUI agent that leverages massive unannotated screenshots and a two-stage curriculum learning framework to reduce reliance on expensive human annotations, achieving competitive performance with advanced systems like UI-TARS using only 0.1% of its data.