arXiv:2509.25170v3 Announce Type: replace-cross Abstract: The performance of flow matching and diffusion models can be greatly improved at inference time using reward alignment algorithms, yet efficiency remains a major limitation. While several algorithms were proposed, we demonstrate that a common bottleneck is the sampling method these algorithms rely on: many algorithms require to sample Markov transitions via SDE sampling, which is significantly less efficient and often less performant than ODE sampling. To remove this bottleneck, we introduce GLASS […]

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Concrete is the most widely used construction material worldwide; however, reliable prediction of compressive strength remains challenging due to material heterogeneity, variable mix proportions, and sensitivity to field and environmental conditions. Recent advances in artificial intelligence enable data-driven modeling frameworks capable of supporting automated decision-making in construction quality control. This study leverages an industry-scale dataset consisting of approximately 70,000 compressive strength test records to evaluate and compare multiple predictive approaches, including linear regression, decision trees, random forests, transformer-based […]

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Imagine this: you’re in a team meeting, and your manager tells you there’s an old service, written a couple of years ago, that used to work fine but now breaks in some weird way. And you need to fix it. On top of that, they ask you to implement a new feature that the team has been wanting for a long time. At this point, your happiness for the next few hours, days, or even weeks largely depends […]

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Nonstationary time series forecasting suffers from the distribution shift issue due to the different distributions that produce the training and test data. Existing methods attempt to alleviate the dependence by, e.g., removing low-order moments from each individual sample. These solutions fail to capture the underlying time-evolving structure across samples and do not model the complex time structure. In this paper, we aim to address the distribution shift in the frequency space by considering all possible time structures. To […]

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Table Of Links Abstract 1 Introduction 2 Background 3 Privacy-Relevant Methods 4 Identifying API Privacy-relevant Methods 5 Labels for Personal Data Processing 6 Process of Identifying Personal Data 7 Data-based Ranking of Privacy-relevant Methods 8 Application to Privacy Code Review 9 Related Work Conclusion, Future Work, Acknowledgement And References Identifying API Privacy-Relevant Methods Native privacy-relevant methods form the basis for identifying what we refer to as API privacyrelevant methods. These are methods found in third-party libraries and frameworks […]

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The fight for educational freedom is as old as America itself and rooted in a deep and enduring tradition of parents and communities shaping how children learn. lead , On December 9th, you can join Cato scholar Neal McCluskey for a live online book forum as he and the Head of Education at the Liberty Branch of the Institute for Governance and Civics at Florida State University, James Shuls, discuss their new book, Fighting for the Freedom to Learn, which […]

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arXiv:2304.05305v2 Announce Type: replace-cross Abstract: We propose a hierarchical tensor-network approach for approximating high-dimensional probability density via empirical distribution. This leverages randomized singular value decomposition (SVD) techniques and involves solving linear equations for tensor cores in this tensor network. The complexity of the resulting algorithm scales linearly in the dimension of the high-dimensional density. An analysis of estimation error demonstrates the effectiveness of this method through several numerical experiments.

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arXiv:2602.11324v1 Announce Type: new Abstract: A key principle in string processing is local consistency: using short contexts to handle matching fragments of a string consistently. String synchronizing sets [Kempa, Kociumaka; STOC 2019] are an influential instantiation of this principle. A $tau$-synchronizing set of a length-$n$ string is a set of $O(n/tau)$ positions, chosen via their length-$2tau$ contexts, such that (outside highly periodic regions) at least one position in every length-$tau$ window is selected. Among their applications are faster […]

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