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arXiv:2603.17468v1 Announce Type: new Abstract: We present GuidedSAC, a novel reinforcement learning (RL) algorithm that facilitates efficient exploration in vast state-action spaces. GuidedSAC leverages large …
arXiv:2603.17478v1 Announce Type: new Abstract: This study explores the combination of automated machine learning (AutoML) with model-based deep unfolding (DU) for optimizing wireless beamforming and …
arXiv:2603.17507v1 Announce Type: new Abstract: Federated Learning (FL) enables privacy-preserving intelligence on Internet of Things (IoT) devices but incurs a significant carbon footprint due to …
arXiv:2603.17523v1 Announce Type: new Abstract: Neural Operators (NOs) are a powerful deep learning framework designed to learn the solution operator that arise from partial differential …
arXiv:2603.15670v1 Announce Type: new Abstract: Real-world decision-making, from tax compliance assessment to medical diagnosis, requires aggregating multiple noisy and potentially contradictory evidence sources. Existing approaches …
arXiv:2603.16307v1 Announce Type: new Abstract: Remote sensing underpins crucial applications such as disaster relief and ecological field surveys, where systems must understand complex scenes and …
arXiv:2603.15666v1 Announce Type: new Abstract: Existing memory systems for language agents address memory management: how to retrieve and page more information within a context budget. …
arXiv:2603.15677v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly central to clinician workflows, spanning clinical decision support, medical education, and patient communication. However, …
arXiv:2603.16210v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is commonly implemented as a single static policy embedded in model parameters. However, …
arXiv:2603.15936v1 Announce Type: new Abstract: ClinicalTrials.gov (CT.gov) is the largest publicly accessible registry of clinical studies, yet its registry-oriented architecture and heterogeneous adverse event (AE) …
arXiv:2603.15848v1 Announce Type: new Abstract: The report presents with the development and optimisation of an enhanced algorithmic trading strategy through the use of historical S&P …
arXiv:2603.15661v1 Announce Type: new Abstract: Large Language Model-based Multi-Agent Systems (MAS) have demonstrated remarkable collaborative reasoning capabilities but introduce new attack surfaces, such as the …