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Rethinking feature fusion, this study reveals that focusing on the differences between feature streams can dramatically enhance U-Net performance across diverse applications.
Joycent synthesizes accented speech directly from standard phone sequences, eliminating the need for error-prone accented phone predictions.
MLLMs excel at precision but falter dramatically in extracting complete product specifications from multiple images, with a mere 49.9% recovery rate.
Temporal coupling in multimodal biomolecular design can dramatically improve the quality and diversity of generated compounds, outperforming conventional methods.
A large-scale, multilingual dataset for online polarization detection is now available, offering a benchmark for future research in this critical area.
