arXiv:2604.10910v2 Announce Type: replace
Abstract: 2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-agnostic or spatio-temporal feature overlapping e…
arXiv:2604.12970v1 Announce Type: cross
Abstract: Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge arises from modality heterogeneity: many clinical …
In 2026, enterprise developers are building and deploying the first generation of powerful, increasingly autonomous AI agents at incredible speed. Now comes the hard part: working out how to secure them.
Vendors in the space a…
arXiv:2508.15452v3 Announce Type: replace-cross
Abstract: Numerous deep learning-based solutions have been developed for the automatic recognition of breast cancer using mammography images. However, their performance often declines when applied to dat…
arXiv:2604.11487v1 Announce Type: new
Abstract: This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE workshop at CVPR 2026. The goal of this challenge was to…
arXiv:2604.10577v1 Announce Type: cross
Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automate harmful actions programmatically. Existing safety…
arXiv:2602.04849v2 Announce Type: replace-cross
Abstract: We present El Agente Estructural, a multimodal, natural-language-driven geometry-generation and manipulation agent for autonomous chemistry and molecular modelling. Unlike molecular generation …
arXiv:2604.02369v3 Announce Type: replace-cross
Abstract: Agent communication protocols are becoming critical infrastructure for large language model (LLM) systems that must use tools, coordinate with other agents, and operate across heterogeneous env…
arXiv:2604.08538v3 Announce Type: replace
Abstract: AI agents are changing the requirements for document parsing. What matters is semantic correctness: parsed output must preserve the structure and meaning needed for autonomous decisions, including co…
arXiv:2604.11389v1 Announce Type: new
Abstract: Reliable recognition of standard cine cardiac MRI views is essential because each view determines which cardiac anatomy is visualized and which quantitative analyses can be performed. Incorrect view iden…