arXiv:2601.21747v3 Announce Type: replace
Abstract: Sepsis remains one of the most complex and heterogeneous syndromes in intensive care, characterized by diverse physiological trajectories and variable responses to treatment. While deep learning mode…
arXiv:2510.09734v2 Announce Type: replace
Abstract: Weather forecasting is a fundamental task in spatiotemporal data analysis, with broad applications across a wide range of domains. Existing data-driven forecasting methods typically model atmospheric…
arXiv:2409.12296v3 Announce Type: replace-cross
Abstract: Inspired by the gradient flow viewpoint of the Landau equation and the corresponding dynamic formulation of the Landau metric in [arXiv:2007.08591], we develop a novel implicit particle method …
arXiv:2603.19835v3 Announce Type: replace
Abstract: We present Future-KL Influenced Policy Optimization (FIPO), a reinforcement learning algorithm designed to overcome reasoning bottlenecks in large language models. While GRPO style training scales ef…
arXiv:2509.06272v4 Announce Type: replace-cross
Abstract: Swarm based optimization algorithms have demonstrated remarkable success in solving complex optimization problems. However, their widespread adoption remains sceptical due to limited transparen…
arXiv:2603.28776v1 Announce Type: new
Abstract: Learning to generate images with internally repeated and periodic structures poses a fundamental challenge for machine learning and computer vision models, which are typically optimised for local texture…
arXiv:2603.28522v2 Announce Type: replace-cross
Abstract: We present LAD, a real-time language–action planner with an interruptible architecture that produces a motion plan in a single forward pass (~20 Hz) or generates textual reasoning alongside a …
arXiv:2603.29660v1 Announce Type: cross
Abstract: Next-generation radio astronomy surveys are producing millions of resolved sources, but robust morphology analysis remains difficult across heterogeneous telescopes and imaging pipelines. We present ST…
arXiv:2603.26320v2 Announce Type: replace-cross
Abstract: Vision–Language–Action (VLA) models that encode actions using a discrete tokenization scheme are increasingly adopted for robotic manipulation, but existing decoding paradigms remain fundamen…
arXiv:2603.29602v1 Announce Type: cross
Abstract: Existing multi-turn image editing paradigms are often confined to isolated single-step execution. Due to a lack of context-awareness and closed-loop feedback mechanisms, they are prone to error accumul…