arXiv:2604.01644v1 Announce Type: new
Abstract: Natural language provides an intuitive way to express spatial intent in geospatial applications. While existing localization methods often rely on dense point cloud maps or high-resolution imagery, OpenS…
arXiv:2604.02055v1 Announce Type: new
Abstract: Accurate reproduction of facial skin tone is essential for realism, identity preservation, and fairness in Virtual Human (VH) rendering. However, most accessible avatar creation pipelines rely on photogr…
arXiv:2603.29966v2 Announce Type: replace
Abstract: Surgical video understanding is essential for computer-assisted interventions, yet existing surgical foundation models remain constrained by limited data scale, procedural diversity, and inconsistent…
arXiv:2503.12797v3 Announce Type: replace
Abstract: Knowledge-Intensive Visual Grounding (KVG) requires models to localize objects using fine-grained, domain-specific entity names rather than generic referring expressions. Although Multimodal Large La…
arXiv:2604.01929v1 Announce Type: cross
Abstract: The audio research community depends on open generative models as foundational tools for building novel approaches and establishing baselines. In this report, we present Woosh, Sony AI’s publicly relea…
arXiv:2604.02073v1 Announce Type: new
Abstract: Universal multimodal embedding (UME) maps heterogeneous inputs into a shared retrieval space with a single model. Recent approaches improve UME by generating explicit chain-of-thought (CoT) rationales be…
arXiv:2604.01676v1 Announce Type: new
Abstract: GUI Process Automation (GPA) is a lightweight but general vision-based Robotic Process Automation (RPA), which enables fast and stable process replay with only a single demo. Addressing the fragility of …
arXiv:2602.23791v2 Announce Type: replace-cross
Abstract: Accurate focus quality assessment (FQA) in fluorescence microscopy is challenging due to stain-dependent optical variations that induce heterogeneous focus behavior across images. Existing meth…
arXiv:2407.17491v3 Announce Type: replace
Abstract: With a surge of large-scale pre-trained models, parameter-efficient transfer learning (PETL) of large models has garnered significant attention. While promising, they commonly rely on two optimistic …
arXiv:2604.01977v1 Announce Type: cross
Abstract: Security teams face a challenge: the volume of newly disclosed Common Vulnerabilities and Exposures (CVEs) far exceeds the capacity to manually develop detection mechanisms. In 2025, the National Vulne…