arXiv:2405.11619v2 Announce Type: replace-cross
Abstract: Phishing emails continue to pose a significant threat, causing financial losses and security breaches. This study addresses limitations in existing research, such as reliance on proprietary dat…
arXiv:2409.09298v2 Announce Type: replace-cross
Abstract: The Matrix Profile (MP), a versatile tool for time series data mining, has been shown effective in time series anomaly detection (TSAD). This paper delves into the problem of anomaly detection …
arXiv:2604.06515v1 Announce Type: cross
Abstract: Sparse Mixture-of-Experts (MoE) allows scaling of language and vision models efficiently by activating only a small subset of experts per input. While this reduces computation, the large number of para…
arXiv:2411.18084v2 Announce Type: replace-cross
Abstract: Mobile apps are essential in daily life but frequently employ deceptive patterns, such as visual emphasis or linguistic nudging, to manipulate user behavior. Existing research largely relies on…
arXiv:2503.17181v3 Announce Type: replace-cross
Abstract: Despite the rapid progress of large language models (LLMs) in code generation, existing evaluations focus on functional correctness or syntactic validity, overlooking how LLMs make critical des…
arXiv:2506.05171v3 Announce Type: replace-cross
Abstract: Embodied AI systems, comprising AI models and physical plants, are increasingly prevalent across various applications. Due to the rarity of system failures, ensuring their safety in complex ope…
arXiv:2604.06566v1 Announce Type: cross
Abstract: As the complexity of modern workloads and hardware increasingly outpaces human research and engineering capacity, existing methods for database performance optimization struggle to keep pace. To addres…
arXiv:2507.18937v3 Announce Type: replace-cross
Abstract: Due to limited computational resources, medium-range temperature forecasts typically rely on low-resolution numerical weather prediction (NWP) models, which are prone to systematic and random e…
arXiv:2508.07299v2 Announce Type: replace-cross
Abstract: The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby enabling the selection of beneficial unsupervised p…
arXiv:2604.06279v1 Announce Type: cross
Abstract: Accurate parameter selection is fundamental to gyrokinetic plasma simulations, yet current practices rely heavily on manual literature reviews, leading to inefficiencies and inconsistencies. We introdu…