GAUC selects coresets in pre-trained VLM embedding space by jointly optimizing distributional fidelity via MMD, prompt robustness via effective mutual information difference, and output stability via predictive variance penalty.
Cancer statistics for the year 2020: An overview
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
TTS data augmentation and LLM error correction together cut relative WER by 40-50% on ASR models for oral cancer speech.
citing papers explorer
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Geometry-Aware Uncertainty Coresets for Robust Visual In-Context Learning in Histopathology
GAUC selects coresets in pre-trained VLM embedding space by jointly optimizing distributional fidelity via MMD, prompt robustness via effective mutual information difference, and output stability via predictive variance penalty.
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Improving Automatic Speech Recognition for Speakers Treated for Oral Cancer using Data Augmentation and LLM Error Correction
TTS data augmentation and LLM error correction together cut relative WER by 40-50% on ASR models for oral cancer speech.