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arXiv:2603.19298v1 Announce Type: new Abstract: Operator situation awareness is a pivotal yet elusive determinant of human reliability in complex nuclear control environments. Existing assessment methods, …
arXiv:2603.19299v1 Announce Type: new Abstract: In recent years, progress in medical informatics and machine learning has been accelerated by the availability of openly accessible benchmark …
arXiv:2603.19302v1 Announce Type: new Abstract: Machine unlearning is increasingly important for clinical language models, where privacy regulations and institutional policies may require removing sensitive information …
arXiv:2603.19307v1 Announce Type: new Abstract: Modeling the complex interactions among functional subnetworks is crucial for the diagnosis of mental disorders and the identification of functional …
arXiv:2603.19308v1 Announce Type: new Abstract: In autonomous driving, multi-agent collaborative perception enhances sensing capabilities by enabling agents to share perceptual data. A key challenge lies …
arXiv:2603.19310v1 Announce Type: new Abstract: Training large language models (LLMs) for complex reasoning via reinforcement learning requires reward labels that specify whether the generated rollouts …
arXiv:2603.19312v1 Announce Type: new Abstract: Joint Embedding Predictive Architectures (JEPAs) offer a compelling framework for learning world models in compact latent spaces, yet existing methods …
arXiv:2603.19314v1 Announce Type: new Abstract: In the modern financial system, combating money laundering is a critical challenge complicated by data privacy concerns and increasingly complex …
arXiv:2603.19315v1 Announce Type: new Abstract: Time series classification (TSC) performance depends not only on architectural design but also on the diversity of input representations. In …
arXiv:2603.19317v1 Announce Type: new Abstract: This paper establishes a theoretical framework connecting neural network learning with abstract algebraic structures. We first present a minimal counterexample …
arXiv:2603.19322v1 Announce Type: new Abstract: While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for problems involving discrete …
arXiv:2603.19325v1 Announce Type: new Abstract: Deep learning models for meteorological forecasting often fail in rare but high-impact events such as typhoons, where relevant data is …
