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arXiv:2602.19390v1 Announce Type: new Abstract: The convergence of modeling & simulation (M&S) and artificial intelligence (AI) is leaving its marks on advanced digital technology. Pertinent...
arXiv:2602.19392v1 Announce Type: new Abstract: Graphs provide a powerful basis for modeling Web-based relational data, with expressive GNNs to support the effective learning in dynamic...
arXiv:2602.19393v1 Announce Type: new Abstract: Steck, Ekanadham, and Kallus [arXiv:2403.05440] demonstrate that cosine similarity of learned embeddings from matrix factorization models can be rendered arbitrary...
arXiv:2602.19395v1 Announce Type: new Abstract: Reconstructing the speech audio envelope from scalp neural recordings (EEG) is a central task for decoding a listener's attentional focus...
arXiv:2602.19396v1 Announce Type: new Abstract: Large language models (LLMs) remain vulnerable to jailbreak prompts that are fluent and semantically coherent, and therefore difficult to detect...
arXiv:2602.19400v1 Announce Type: new Abstract: We present a coverage framework that integrates Hilbert space-filling priors into decentralized multi-robot learning and execution. We augment DQN and...
arXiv:2602.19401v1 Announce Type: new Abstract: Obsessive Compulsive Disorder (OCD) is a mental health disorder characterized by distressing repetitive patterns of thought, referred to as obsessions,...
arXiv:2602.19404v1 Announce Type: new Abstract: The rise of app-based ride-sharing has fundamentally changed tipping culture in New York City. We analyzed 280 million trips from...
arXiv:2602.19406v1 Announce Type: new Abstract: Long-range geophysical forecasts are fundamentally limited by chaotic dynamics and numerical errors. While data assimilation can mitigate these issues, classical...
arXiv:2602.19407v1 Announce Type: new Abstract: Large language models demonstrate strong capabilities in code generation but struggle to navigate complex, multi-language repositories to locate relevant code....
arXiv:2602.19408v1 Announce Type: new Abstract: In computational genomics, many analyses rely on efficient storage and traversal of $k$-mers, motivating compact representations such as spectrum-preserving string...
arXiv:2602.19409v1 Announce Type: new Abstract: Manual annotation of audio datasets is labour intensive, and it is challenging to balance label granularity with acoustic separability. We...
arXiv:2602.19410v1 Announce Type: new Abstract: Modern organizations increasingly face cybersecurity incidents driven by human behaviour rather than technical failures. To address this, we propose a...
arXiv:2602.19412v1 Announce Type: new Abstract: U-Net architectures have been instrumental in advancing biomedical image segmentation (BIS) but often struggle with capturing long-range information. One reason...
arXiv:2602.19414v1 Announce Type: new Abstract: Networks of interdependent industrial assets (clients) are tightly coupled through physical processes and control inputs, raising a key question: how...
arXiv:2602.19416v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) enables powerful LLM alignment but can introduce reward hacking - models exploit spurious correlations...
arXiv:2602.19418v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) are foundational to modern multimodal applications, yet their susceptibility to adversarial attacks remains a critical concern....
arXiv:2602.19419v1 Announce Type: new Abstract: Concentrated liquidity provision in decentralized exchanges presents a fundamental Impulse Control problem. Liquidity Providers (LPs) face a non-trivial trade-off between...
arXiv:2602.19421v1 Announce Type: new Abstract: Transmission expansion planning in electricity markets is tightly coupled with the strategic bidding behaviors of generation companies. This paper proposes...
arXiv:2602.19422v1 Announce Type: new Abstract: Design-oriented HRI is increasingly interested in robots as long-term companions, yet many designs still assume a fixed form and a...
arXiv:2602.19423v1 Announce Type: new Abstract: Domain adaptive segmentation (DAS) is a promising paradigm for delineating intracellular structures from various large-scale electron microscopy (EM) without incurring...
arXiv:2602.19424v1 Announce Type: new Abstract: Hepatocellular Carcinoma diagnosis relies heavily on the interpretation of gigapixel Whole Slide Images. However, current computational approaches are constrained by...
arXiv:2602.19428v1 Announce Type: new Abstract: This paper proposes a novel computationally efficient algorithm for optimal sizing of Battery Energy Storage Systems (BESS) considering renewable energy...
arXiv:2602.19430v1 Announce Type: new Abstract: Despite the inherent advantages of thermal infrared(TIR) imaging, large-scale data collection and annotation remain a major bottleneck for TIR-based perception....