arXiv:2601.20015v1 Announce Type: new Abstract: DBTuneSuite is a suite of experiments on four widely deployed free database systems to test their performance under various query/upsert loads and under various tuning options. The suite provides: (i) scripts to generate data and to install and run tests, making it expandable to other tests and systems; (ii) suggestions of which systems work best for which query types; and (iii) quantitative evidence that tuning options widely used in practice can behave very […]

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arXiv:2603.23565v1 Announce Type: new Abstract: Safe reinforcement learning (RL) is a standard paradigm for safety-critical decision making. However, real-world safety constraints can be complex, subjective, and even hard to explicitly specify. Existing works on constraint inference rely on restrictive assumptions or extensive expert demonstrations, which is not realistic in many real-world applications. How to cheaply and reliably learn these constraints is the major challenge we focus on in this study. While inferring constraints from human preferences offers a […]

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arXiv:2601.17050v1 Announce Type: new Abstract: Adverse social interactions, such as bullying, harassment, and other illicit activities, pose significant threats to individual well-being and public safety, leaving profound impacts on physical and mental health. However, these critical events frequently occur in privacy-sensitive environments like restrooms, and changing rooms, where conventional surveillance is prohibited or severely restricted by stringent privacy regulations and ethical concerns. Here, we propose the Single-Pixel Vision-Language Model (SP-VLM), a novel framework that reimagines secure environmental monitoring. […]

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Weight-space models learn directly from the parameters of neural networks, enabling tasks such as predicting their accuracy on new datasets. Naive methods — like applying MLPs to flattened parameters — perform poorly, making the design of better weight-space architectures a central challenge. While prior work leveraged permutation symmetries in standard networks to guide such designs, no analogous analysis or tailored architecture yet exists for Kolmogorov-Arnold Networks (KANs). In this work, we show that KANs share the same permutation […]

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Chelsea Follett The debut of the robot butler NEO has drawn widespread ridicule. Unable to perform many chores without a remote human operator, the machine has become a target of social media backlash. Videos circulating online show the robot struggling with basic tasks, such as closing a dishwasher. , But don’t underestimate the potential of robotic housekeepers just yet. The technology is dawning at an opportune time. Consider the growing concerns about plummeting birth rates. Last year saw […]

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arXiv:2603.16798v1 Announce Type: cross Abstract: We study mean estimation for a Gaussian distribution with identity covariance in $mathbb{R}^d$ under a missing data scheme termed realizable $epsilon$-contamination model. In this model an adversary can choose a function $r(x)$ between 0 and $epsilon$ and each sample $x$ goes missing with probability $r(x)$. Recent work Ma et al., 2024 proposed this model as an intermediate-strength setting between Missing Completely At Random (MCAR) — where missingness is independent of the data — […]

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arXiv:2601.02535v1 Announce Type: new Abstract: Selecting a single high-quality output from multiple stochastic generations remains a fundamental challenge for large language models (LLMs), particularly in open-ended tasks where no canonical answer exists. While Best-of-N and self-consistency methods show that aggregating multiple generations can improve performance, existing approaches typically rely on external evaluators, reward models, or exact string-match voting, limiting their applicability and efficiency. We propose Mode Extraction (ModeX), an evaluator-free Best-of-N selection framework that generalizes majority voting to […]

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India’s AQI crisis sees no signs of abating. All across northern India, the winter season sees the AQI stay in the very hazardous category for months together across the big cities, small towns, and even villages of North India. AQI readings above 400 are routine, and one has come to regard a 150 AQI, which constitutes the poor category, as pretty much normal and par for the course. The fact that the high AQI levels have started getting […]

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We design a deep reinforcement learning algorithm to explore a high-dimensional integer lattice with sparse rewards, training a feedforward neural network as a dynamic search heuristic to steer exploration toward reward dense regions. We apply this to the discovery of Fano 4-fold hypersurfaces with terminal singularities, objects of central importance in algebraic geometry. Fano varieties with terminal singularities are fundamental building blocks of algebraic varieties, and explicit examples serve as a vital testing ground for the development and […]

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Why the seeds of the next civilization are already growing, and how to see them. What if the chaos around us isn’t collapse, but transformation? Michel Bauwens has spent decades mapping the edges of change. From peer-to-peer networks to the commons, from medieval guilds to distributed autonomous organizations, he’s been tracking something most people miss: the seeds of a new civilization, already growing underneath the noise. Some people might call Bauwens a unicorn, because he does not fit […]

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