arXiv:2604.23903v1 Announce Type: cross
Abstract: Large-scale neuroscience is generating rich datasets across animals, brain areas and behavioral contexts, yet our modeling efforts remains fragmented across isolated experiments. We argue that understa…
arXiv:2601.18399v2 Announce Type: replace
Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone height is an important performance and safety indicato…
Microsoft and OpenAI on Monday again revised their agreement, softening their exclusivity and revenue-sharing conditions in the process. These changes underscore how critical it is for enterprises to work with as many AI vendors …
arXiv:2604.22281v1 Announce Type: new
Abstract: Recent advances in vision-language models have demonstrated remarkable performance across diverse multi-modal tasks, including document question answering that leverages structured visual cues from text,…
arXiv:2604.20046v2 Announce Type: replace
Abstract: 3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gaussian primitives. However, it suffers from a subs…
arXiv:2604.22739v1 Announce Type: new
Abstract: Social interactions dominate our perceptions of the world and shape our daily behavior by attaching social meaning to acts as simple and spontaneous as gestures, facial expressions, voice, and speech. Pe…
arXiv:2604.22390v1 Announce Type: new
Abstract: Visual Place Recognition (VPR) determines a query image’s geographic location by matching it against geotagged databases. However, existing methods struggle with perceptual aliasing caused by irrelevant …
arXiv:2604.22409v1 Announce Type: new
Abstract: Multimodal large language models (MLLMs) have advanced static visual–spatial reasoning, yet they often fail to preserve long-horizon spatial coherence in embodied settings where beliefs must be continuo…
arXiv:2604.22482v1 Announce Type: new
Abstract: While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Moreover, existing panoramic 3D datasets are predomin…
arXiv:2604.22506v1 Announce Type: new
Abstract: Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compression artifacts, and adverse imaging conditions ca…