arXiv:2604.06722v1 Announce Type: cross
Abstract: Embodied AI for Science (EAI4S) brings intelligence into the laboratory by uniting perception, reasoning, and robotic action to autonomously run experiments in the physical world. For the Global South,…
arXiv:2604.06876v1 Announce Type: cross
Abstract: Multi-robot systems are becoming increasingly relevant within diverse application domains, such as healthcare, exploration, and rescue missions. However, building such systems is still a significant ch…
arXiv:2309.08780v2 Announce Type: replace
Abstract: Due to the challenges regarding the limits of their endurance and autonomous capabilities, underwater docking for autonomous underwater vehicles (AUVs) has become a topic of interest for many academi…
arXiv:2511.18525v2 Announce Type: replace
Abstract: We present Splatblox, a real-time system for autonomous navigation in outdoor environments with dense vegetation, irregular obstacles, and complex terrain. Our method fuses segmented RGB images and L…
arXiv:2602.16005v2 Announce Type: replace-cross
Abstract: We introduce ODYN, a novel all-shifted primal-dual non-interior-point quadratic programming (QP) solver designed to efficiently handle challenging dense and sparse QPs. ODYN combines all-shifte…
arXiv:2604.05828v2 Announce Type: replace
Abstract: Precise aggressive maneuvers with lightweight onboard sensors remains a key bottleneck in fully exploiting the maneuverability of drones. Such maneuvers are critical for expanding the systems’ access…
arXiv:2604.07335v1 Announce Type: new
Abstract: Handheld paradigms offer an efficient and intuitive way for collecting large-scale demonstration of robot manipulation. However, achieving contact-rich bimanual manipulation through these methods remains…
arXiv:2604.06277v1 Announce Type: new
Abstract: Existing hallucination detection methods for large language models (LLMs) rely on external verification at inference time, requiring gold answers, retrieval systems, or auxiliary judge models. We ask whe…
arXiv:2604.06251v1 Announce Type: new
Abstract: This article presents the results of a data science study conducted at a container terminal, aimed at reducing unproductive container moves through the prediction of service requirements and container dw…
arXiv:2604.06628v1 Announce Type: new
Abstract: A prevailing narrative in LLM post-training holds that supervised finetuning (SFT) memorizes while reinforcement learning (RL) generalizes. We revisit this claim for reasoning SFT with long chain-of-thou…