arXiv:2510.27324v1 Announce Type: cross Abstract: We consider the problem of ultra-low bit rate visual communication for remote vision analysis, human interactions and control in challenging

arXiv:2510.27222v1 Announce Type: cross Abstract: Equivariant representation learning aims to capture variations induced by input transformations in the representation space, whereas invariant representation learning encodes

arXiv:2510.27267v1 Announce Type: cross Abstract: As large language models (LLMs) enter the medical domain, most benchmarks evaluate them on question answering or descriptive reasoning, overlooking

arXiv:2510.27128v1 Announce Type: cross Abstract: Recent advances in neural decoding have enabled the reconstruction of visual experiences from brain activity, positioning fMRI-to-image reconstruction as a

arXiv:2510.27186v1 Announce Type: cross Abstract: Model inversion, which aims to reconstruct the original training data from pre-trained discriminative models, is especially useful when the original