arXiv:2601.19925v1 Announce Type: new Abstract: Introduction: Large language models (LLMs) can process requests and generate texts, but their feasibility for assessing complex academic content needs further investigation. To explore LLM’s potential in assisting scientific review, this study examined ChatGPT-5, Gemini-3-Pro, and Claude-Sonnet-4.5’s consistency and reliability in evaluating abstracts compared to one another and to human reviewers. Methods: 160 abstracts from a local conference were graded by human reviewers and three LLMs using one rubric. Composite score distributions across […]

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Introduction: The Reality of the Build: A Post-Mortem We were building a multi-lens introspection system designed to take a user’s inner state and translate it into structured insights. At a certain point in development, the system just stopped producing outputs. It didn’t crash—but it started timing out, again and again. And when it didn’t time out, it went silent: no insights, no partial responses, no recoverable errors. Just empty. We treated it as an engineering problem. We audited […]

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Ontario, Canada, April 6th, 2026, Chainwire CoinRabbit Cuts Crypto Lending Rates CoinRabbit has lowered crypto lending rates, which now start at 11.95%. The platform offers a range of liquidation LTV options, from a standard market setup at 80% to a more conservative risk management approach at 90–95%. This is one of the most competitive offers in the CeFi lending space, in terms of interest rates and loan terms. What Reduced Crypto Lending Rates Actually Mean CoinRabbit announces a […]

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arXiv:2605.24072v1 Announce Type: new Abstract: Finite-width fully connected neural networks with Gaussian-initialized weights deviate from their infinite-width Gaussian limit, exhibiting non-vanishing higher-order cumulants. We approximate these deviations, for a neural network evaluated in a finite number of inputs, using multidimensional Edgeworth expansions of arbitrary order $4m-1$, with $minmathbb{N}$. Assuming that the corresponding Gaussian limit has an invertible covariance matrix and that the activation function is polynomially bounded, we establish a bound of order $n^{-m}$ on the total variation […]

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arXiv:2604.07467v1 Announce Type: new Abstract: Discrete speech units (DSUs) are derived by quantising representations from models trained using self-supervised learning (SSL). They are a popular representation for a wide variety of spoken language tasks, including those where prosody matters. DSUs are especially convenient for tasks where text and speech are jointly modelled, such as text-to-speech and multimodal dialogue systems. But we have found that DSUs encode suprasegmental information less reliably than segmental structure, which we demonstrate in this […]

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arXiv:2402.03352v3 Announce Type: replace-cross Abstract: In this paper, we study zeroth-order algorithms for nonconvex minimax problems with coupled linear constraints under the deterministic and stochastic settings, which have attracted wide attention in machine learning, signal processing and many other fields in recent years, e.g., adversarial attacks in resource allocation problems and network flow problems etc. We propose two single-loop algorithms, namely the zeroth-order primal-dual alternating projected gradient (ZO-PDAPG) algorithm and the zeroth-order regularized momentum primal-dual projected gradient algorithm […]

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arXiv:2602.18500v1 Announce Type: new Abstract: Accurate volumetric characterization of lesions is essential for oncologic diagnosis, risk stratification, and treatment planning. While imaging modalities such as Computed Tomography provide high-quality 3D data, 2D ultrasound (2D-US) remains the preferred first-line modality for breast and thyroid imaging due to cost, portability, and safety factors. However, volume estimates derived from 2D-US suffer from high inter-user variability even among experienced clinicians. Existing 3D ultrasound (3D-US) solutions use specialized probes or external tracking hardware, […]

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The gap between fast-moving AI agents and slow traditional capital formation is no longer sustainable. Founders can now build and scale agentic ventures at unprecedented speed, yet raising capital, structuring governance, and aligning incentives still drag projects down with delays, misaligned tokens, and outdated models. Fresh off research into onchain capital formation and decision markets, Olayimika Oyebanji sat down with Umia co-founder Francesco Mosterts to discuss why today’s tokens are broken, how continuous market-driven governance can fix it, […]

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arXiv:2603.24716v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has revolutionized real-time rendering with its state-of-the-art novel view synthesis, but its utility for accurate geometric measurement remains underutilized. Compared to multi-view stereo (MVS) point clouds or meshes, 3DGS rendered views present superior visual quality and completeness. However, current point measurement methods still rely on demanding stereoscopic workstations or direct picking on often-incomplete and inaccurate 3D meshes. As a novel view synthesizer, 3DGS renders exact source views and smoothly […]

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arXiv:2605.10966v1 Announce Type: new Abstract: Terminals provide a powerful interface for AI agents by exposing diverse tools for automating complex workflows, yet existing terminal-agent benchmarks largely focus on tasks grounded in text, code, and structured files. However, many real-world workflows require practitioners to work directly with audio and video files. Working with such multimedia files calls for terminal agents not only to understand multimedia content, but also to convert auditory and visual evidence across related files into appropriate […]

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