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arXiv:2410.18424v3 Announce Type: replace Abstract: The stringent regulatory requirements on nitrogen oxides (NOx) emissions from diesel compression ignition engines require accurate and reliable models for...
arXiv:2411.03941v3 Announce Type: replace Abstract: Missing values are pervasive in large-scale time-series data, posing challenges for reliable analysis and decision-making. Many neural architectures have been...
arXiv:2411.06657v2 Announce Type: replace Abstract: In the past several years there has been an explosion of available models for vision-language (VL) tasks. Unfortunately, the literature...
arXiv:2411.09244v3 Announce Type: replace Abstract: Solving multiscale diffusion problems is often computationally expensive due to the spatial and temporal discretization challenges arising from high-contrast coefficients....
arXiv:2411.09847v2 Announce Type: replace Abstract: There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is...
arXiv:2411.13493v2 Announce Type: replace Abstract: In 1948, Shannon used a probabilistic argument to show the existence of codes achieving a maximal rate defined by the...
arXiv:2411.17237v4 Announce Type: replace Abstract: The development of multimodal large language models (MLLMs) enables the evaluation of image quality through natural language descriptions. This advancement...
arXiv:2412.12113v3 Announce Type: replace Abstract: Surface water mixed with wastewater creates serious environmental concerns, particularly in densely populated urban areas with inadequate infrastructure. Such contamination...
arXiv:2412.15042v2 Announce Type: replace Abstract: The popularity of the Rust language continues to explode; yet, many critical codebases remain authored in C. Automatically translating C...
arXiv:2501.08449v2 Announce Type: replace Abstract: Protecting an individual's privacy when releasing their data is inherently an exercise in relativity, regardless of how privacy is qualified...
arXiv:2501.12032v3 Announce Type: replace Abstract: The real-time performance of recommender models depends on the continuous integration of massive volumes of new user interaction data into...
arXiv:2501.16443v2 Announce Type: replace Abstract: While deep reinforcement learning (RL) from pixels has achieved remarkable success, its sample inefficiency remains a critical limitation for real-world...
arXiv:2502.00944v4 Announce Type: replace Abstract: Graph neural networks (GNN) have shown promising results for several domains such as materials science, chemistry, and the social sciences....
arXiv:2502.11684v3 Announce Type: replace Abstract: Mathematical reasoning represents a critical frontier in advancing large language models (LLMs). While step-by-step approaches have emerged as the dominant...
arXiv:2502.12981v3 Announce Type: replace Abstract: We present Riemannian Gaussian Variational Flow Matching (RG-VFM), a geometric extension of Variational Flow Matching (VFM) for generative modeling on...
arXiv:2502.13854v3 Announce Type: replace Abstract: In this paper, we study the problem of certifying whether a graph is bipartite (i.e. $2$-colorable) with a locally checkable...
arXiv:2502.14183v3 Announce Type: replace Abstract: Managing Type 1 Diabetes (T1D) demands constant vigilance as individuals strive to regulate their blood glucose levels and avoid dysglycemia,...
arXiv:2502.18424v2 Announce Type: replace Abstract: Language models (LMs) excel at tasks across diverse domains, yet require substantial computational resources during inference. Compression techniques such as...
arXiv:2502.18615v3 Announce Type: replace Abstract: We present an integrated (or end-to-end) framework for the Real2Sim2Real problem of manipulating deformable linear objects (DLOs) based on visual...
arXiv:2503.02308v2 Announce Type: replace Abstract: Smartwatches offer powerful features, but their small touchscreens limit the expressiveness of the input that can be achieved. To address...
arXiv:2503.02310v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models demonstrate remarkable potential for generalizable robotic manipulation. The performance of VLA models can be improved by integrating...
arXiv:2503.03178v4 Announce Type: replace Abstract: With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the...
arXiv:2503.05236v2 Announce Type: replace Abstract: Recent advances in human preference alignment have significantly improved multimodal generation and understanding. A key approach is to train reward...
arXiv:2503.06692v5 Announce Type: replace Abstract: Advanced reasoning in large language models has achieved remarkable performance on challenging tasks, but the prevailing long-context reasoning paradigm faces...