arXiv:2604.18593v1 Announce Type: new Abstract: This paper presents the design of HELIX, an end-to-end verified code generation system with a focus on the intersection of high-performance and high-assurance numerical computing. The code generation can be fine-tuned to generate efficient code for a broad set of computer architectures while providing formal guarantees of the correctness of such generated code. Using a real-life example of a cyber-physical robot system, this paper demonstrates how, by using HELIX, one can start from […]

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Mesh-free numerical methods provide flexible discretisations for complex geometries; however, classical meshless discrete differential operators typically trade low computational cost for limited accuracy or high accuracy for substantial per-stencil computation. We introduce a parametrised framework for learning mesh-free discrete differential operators using a graph neural network trained via polynomial moment constraints derived from truncated Taylor expansions. The model maps local stencils relative positions directly to discrete operator weights. The current work demonstrates that neural networks can learn classical […]

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I don’t “clock out.” I’m 22. I work all day, every day, whenever inspiration strikes. My brain is constantly spinning up new architectures, new stories, and new code. But at 3:30 PM PST, everything stops. That is “Loved Ones Time.” It is the only sacred block in my calendar. And because my brain has been running at 100mph since sunrise, the last thing I have the mental bandwidth for is fighting a user interface. We’ve all been there. […]

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In late 2025, iOS 26 shipped a keyboard that couldn’t keep up with fast typists. Type quickly and characters would go missing. The tap registered, the key animated, but the letter never landed in the field. Worse, the half-finished words poisoned autocorrect, which kept “fixing” text the user never typed. Apple patched it in iOS 26.4 in March 2026. n React Native has its own version of this bug. It’s older than iOS 26’s, it’s still in your […]

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simonw/browser-compat-db Inspired by Mozilla’s new MDN MCP service – source code here – I decided to try converting their comprehensive mdn/browser-compat-data repository full of browser compatibility data into a SQLite database. This new GitHub repo includes a Claude Code for web (Opus 4.8) generated script for doing that using sqlite-utils. I wanted the resulting ~66MB SQLite database to be available via the GitHub CDN with open CORS headers. GitHub releases don’t have those, but any file stored in […]

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arXiv:2602.12316v1 Announce Type: new Abstract: Frontier AI systems are increasingly capable and deployed in high-stakes multi-agent environments. However, existing AI safety benchmarks largely evaluate single agents, leaving multi-agent risks such as coordination failure and conflict poorly understood. We introduce GT-HarmBench, a benchmark of 2,009 high-stakes scenarios spanning game-theoretic structures such as the Prisoner’s Dilemma, Stag Hunt and Chicken. Scenarios are drawn from realistic AI risk contexts in the MIT AI Risk Repository. Across 15 frontier models, agents choose […]

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arXiv:2603.15802v1 Announce Type: new Abstract: In many time series forecasting settings, the target time series is accompanied by exogenous covariates, such as promotions and prices in retail demand; temperature in energy load; calendar and holiday indicators for traffic or sales; and grid load or fuel costs in electricity pricing. Ignoring these exogenous signals can substantially degrade forecasting accuracy, particularly when they drive spikes, discontinuities, or regime and phase changes in the target series. Most current time series foundation […]

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arXiv:2603.12433v2 Announce Type: new Abstract: Model stitching, connecting early layers of one model (source) to later layers of another (target) via a light stitch layer, has served as a probe of representational compatibility. Prior work finds that models trained on the same dataset remain stitchable (negligible accuracy drop) despite different initializations or objectives. We revisit stitching for Vision Foundation Models (VFMs) that vary in objectives, data, and modality mix (e.g., CLIP, DINOv2, SigLIP 2) and ask: Are heterogeneous […]

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arXiv:2601.22204v1 Announce Type: new Abstract: Federated learning (FL) encounters substantial challenges due to heterogeneity, leading to gradient noise, client drift, and partial client participation errors, the last of which is the most pervasive but remains insufficiently addressed in current literature. In this paper, we propose FedAdaVR, a novel FL algorithm aimed at solving heterogeneity issues caused by sporadic client participation by incorporating an adaptive optimiser with a variance reduction technique. This method takes advantage of the most recent […]

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arXiv:2603.10020v1 Announce Type: new Abstract: Dark patterns in online commerce, especially deceptive user interface designs for apps and websites, undermine consumer autonomy and distort online markets. Although sometimes deception is intentional, the complex app development process can also unintentionally produce manipulative user interfaces. This paper discusses common design pitfalls and proposes strategies for app makers to avoid infringing user autonomy or incurring legal liability under emerging principles of consumer protection law. By focusing on choice architecture and transparent […]

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