CXR-LT 2026 introduces a radiologist-annotated multi-center dataset of 145k+ CXRs to benchmark robust multi-label classification on known classes and open-world generalization to unseen rare diseases.
Reproducible scaling laws for contrastive language-image learning
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Continuous diffusion spoken language models follow scaling laws for loss and phoneme divergence and generate emotive multi-speaker speech at 16B scale, though long-form coherence stays difficult.
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CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification
CXR-LT 2026 introduces a radiologist-annotated multi-center dataset of 145k+ CXRs to benchmark robust multi-label classification on known classes and open-world generalization to unseen rare diseases.
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Scaling Properties of Continuous Diffusion Spoken Language Models
Continuous diffusion spoken language models follow scaling laws for loss and phoneme divergence and generate emotive multi-speaker speech at 16B scale, though long-form coherence stays difficult.