arXiv:2604.23179v1 Announce Type: cross
Abstract: Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization analysis. While mobile robot teams offer the potenti…
arXiv:2511.17411v2 Announce Type: replace
Abstract: Robotic Foundation Models (RFMs) hold great promise as generalist, end-to-end systems for robot control. Yet their ability to generalize across new environments, tasks, and embodiments remains limite…
arXiv:2604.23609v1 Announce Type: new
Abstract: Contact-rich manipulation is central to many everyday human activities, requiring continuous adaptation to contact uncertainty and external disturbances through multi-modal perception, particularly visio…
arXiv:2602.12971v2 Announce Type: replace
Abstract: Driven by recent advancements in foundation models, semantic scene graphs have emerged as a promising paradigm for high-level 3D environmental abstraction in robot navigation. However, existing frame…
arXiv:2604.22858v1 Announce Type: new
Abstract: Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment directly influence treatment selection and patient survi…
arXiv:2604.23187v1 Announce Type: cross
Abstract: This work introduces DyABD, a novel and complex benchmark dataset of dynamic abdominal MRIs from patients with abdominal hernias and associated high quality abdominal muscle annotations. DyABD is the f…
arXiv:2603.29957v3 Announce Type: replace-cross
Abstract: Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer. However, this approach suffers from critical lim…
arXiv:2504.10527v2 Announce Type: replace
Abstract: Artificial Intelligence (AI) has become essential for analyzing complex data and solving highly-challenging tasks. It is being applied across numerous disciplines beyond computer science, including F…
arXiv:2506.20332v4 Announce Type: replace
Abstract: Vision-language model-based mobile agents have gained the ability to understand complex instructions and mobile screenshots, benefiting from reinforcement learning paradigms like Group Relative Polic…
arXiv:2510.14978v2 Announce Type: replace
Abstract: Recent image editing models have achieved impressive results while following natural language editing instructions, but they rely on supervised fine-tuning with large datasets of input-target pairs. …