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arXiv:2604.05168v1 Announce Type: new Abstract: Leadership-class HPC systems generate massive volumes of heterogeneous, largely unstructured system logs. Because these logs originate from diverse software, hardware, …
arXiv:2604.05070v1 Announce Type: new Abstract: Simulation is essential for autonomous driving, yet current frameworks often model vehicles as rigid assets and fail to capture part-level …
arXiv:2604.05552v1 Announce Type: new Abstract: Large Language Models demonstrate outstanding performance in many language tasks but still face fundamental challenges in managing the non-linear flow …
arXiv:2604.05114v1 Announce Type: new Abstract: We study a pipeline that curates reasoning data from initial structured data for improving long-context reasoning in large language models …
arXiv:2604.05165v1 Announce Type: new Abstract: Reconfigurable Intelligent Surfaces (RIS) has a potential to engineer smart radio environments for next-generation millimeter-wave (mmWave) networks. However, the prohibitive …
arXiv:2604.05700v1 Announce Type: new Abstract: High-fidelity modeling of turbulent flows requires capturing complex spatiotemporal dynamics and multi-scale intermittency, posing a fundamental challenge for traditional knowledge-based …
arXiv:2604.05536v1 Announce Type: new Abstract: Natural language is a complex system that exhibits robust statistical regularities. Here, we represent text as a trajectory in a …
arXiv:2604.05257v1 Announce Type: new Abstract: Diffusion models are increasingly being utilised to create synthetic tabular and time series data for privacy-preserving augmentation. Tabular Denoising Diffusion …
arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researchers …
arXiv:2604.05302v1 Announce Type: new Abstract: Text simplification supports second language (L2) learning by providing comprehensible input, consistent with the Input Hypothesis. However, constructing personalized parallel …
arXiv:2604.05543v1 Announce Type: new Abstract: Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasting addresses this by …
arXiv:2604.05157v1 Announce Type: new Abstract: Computer-Use Agents (CUAs) leverage large language models to execute GUI operations on desktop environments, yet they generate actions without evaluating …