arXiv:2601.03332v1 Announce Type: new Abstract: Kolmogorov–Arnold Networks (KAN) replace scalar weights by learnable univariate functions, often implemented with B-splines. This design can be accurate and interpretable, but it makes inference expensive on CPU because each layer requires many spline evaluations. Standard quantization toolchains are also hard to apply because the main computation is not a matrix multiply but repeated spline basis evaluation. This paper introduces LUT-KAN, a segment-wise lookup-table (LUT) compilation and quantization method for PyKAN-style KAN layers. […]

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How are you, hacker? 🪐 What’s happening in tech today, April 5, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, we present you with these top quality stories. From When Supply Is Just Code: Why Traditional Supply Demand Shouldnt Apply to Digital Money to The Ultimate C# QR Code Library Comparison for 2026, let’s dive right in. What is Agentic Testing? By @qatech [ 6 Min read ] If your test […]

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A more comprehensive approach to probability studies an infinite number of probability laws that are formally admissible. Thus, an infinite number of weighted averages can be handled. Areinterpretation of the central limit theorem is accordingly shown. The deviations or errors from a fixed value are calculated. It is proved that they are normally distributed. Furthermore, such deviations are invariant with respect to geometric translations identifying repeated samples. In this paper, the way of understanding the statistical model to […]

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arXiv:2604.25924v1 Announce Type: new Abstract: Large Language Models have been increasingly employed in the creation of Virtual Assistants due to their ability to generate human-like text and handle complex inquiries. While these models hold great promise, challenges such as hallucinations, missing information, and the difficulty of providing accurate and context-specific responses persist, particularly when applied to highly specialized content domains. In this paper, we focus on addressing these challenges by developing a virtual assistant designed to support students […]

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arXiv:2602.04270v1 Announce Type: cross Abstract: Many fields collect large-scale temporal data through repeated measurements (trials), where each trial is labeled with a set of metadata variables spanning several categories. For example, a trial in a neuroscience study may be linked to a value from category (a): task difficulty, and category (b): animal choice. A critical challenge in time-series analysis is to understand how these labels are encoded within the multi-trial observations, and disentangle the distinct effect of each […]

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Our AI started a cafe in Stockholm Andon Labs previously started an AI-run retail store in San Francisco. Now they’re running a similar experiment in Stockholm, Sweden, only this time it’s a cafe. These experiments are interesting, and often throw out amusing anecdotes: During the first week of inventory, Mona ordered 120 eggs even though the café has no stove. When the staff told her they couldn’t cook them, she suggested using the high-speed oven, until they pointed […]

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Deep Neural Networks (DNNs) are increasingly utilized in high-stakes domains like medical diagnostics and autonomous driving where model reliability is critical. However, the research landscape for ensuring this reliability is terminologically fractured across communities that pursue the same goal of ensuring models rely on causally relevant features rather than confounding signals. While frameworks such as distributionally robust optimization (DRO), invariant risk minimization (IRM), shortcut learning, simplicity bias, and the Clever Hans effect all address model failure due to […]

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arXiv:2601.08972v1 Announce Type: new Abstract: The rapid proliferation of VTubers, digital avatars controlled and voiced by human actors (Nakanohito), has created a lucrative and popular entertainment ecosystem. However, the prevailing industry model, where corporations retain ownership of the VTuber persona while the Nakanohito bears the immense pressure of dual-identity management, exposes the Nakanohito to significant vulnerabilities, including burnout, harassment, and precarious labor conditions. When these pressures become untenable, the Nakanohito may terminate their contracts and later debut with […]

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arXiv:2601.14461v1 Announce Type: new Abstract: The Fokker-Planck (FP) particle method accelerates rarefied-gas simulations by replacing the binary collisions of the commonly used Direct Simulation Monte Carlo (DSMC) method with a drift=diffusion process. Like all particle methods, the FP method is inherently stochastic, which leads to statistical fluctuations in macroscopic quantities and necessitates large particle numbers for accurate results. In this work, we investigate the use of quasi-random numbers, which sample distributions more evenly and thereby reduce the variance. […]

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