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Achieve more stable and accurate alignment of preoperative liver models with intraoperative laparoscopic views by explicitly modeling reliable 2D-3D geometric correspondences supported by latent evidence.
Chemical modifications to proteins, often missed by standard protein language models, can now be accurately captured and leveraged for improved biomolecule design, thanks to a new framework that fuses atomic-level details with broader sequence context.
Achieve SOTA detail-preserving human-product image generation by using a new attention mechanism and loss function, trained on a new large-scale dataset.
