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The integrity of scientific literature depends critically on accurate citations, yet miscitation—where references fail to support cited claims—remains a pervasive problem. Existing detection approaches based on semantic similarity or graph anomaly detection struggle with nuanced logical relationships and multi-hop reasoning, while LLM-based methods face hallucination risks and prohibitive computational costs. Moreover, current LLM agent architectures rely on unconstrained generation, lacking verifiable and safe execution guarantees. We propose CiteGuard, a multi-agent framework that unifies chain-of-evidence reasoning, graph-enhanced detection, and […]

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We prove strict log-concavity of the Riemann-Jacobi kernel, establish hyperbolicity of the Jensen polynomials J_{d,n}(x) for d <= 22, n <= 14, and prove that the global Riemann Hypothesis is algebraically equivalent to a subluminal condition on the Wronskian components. Part I (Sections 2-5) proves the kernel is strictly log-concave (TP_2) with curvature kappa >= 19.24, via the convex potential decomposition and a perturbation bound using only 4.3% of the log-concavity budget. Part II (Sections 6-8) establishes K_{d,n}(x) […]

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In this Part 2 of the paper, analytical, parametric multi-step solution is given of all of the six area and moments integrals of arbitrary segment of ellipse defined in parametrical form by trigonometric functions, based on its corresponding integrals of its central sector from Part 1 of the paper. Those integrals are here built from the general moment form of Green’s theorem curve integral for the calculation of the area and moments of a planar shape enclosed by […]

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What happens when you stop throwing money at AI infrastructure and start thinking about architecture instead A third-party cost analysis priced the platform at $32,000. The prototype went from concept to production deployment in six hours. Total compute cost for the first full cognitive evaluation session: less than one cent. Those numbers are not a rounding error. They are the result of a fundamental architectural decision that most AI developers never consider: what if the intelligence isn’t in […]

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The software engineering industry relies heavily on Large Language Models (LLMs) accessed via flat-rate web subscriptions, operating under the assumption of infinite, highly available compute. However, the paradigm of “unlimited compute” is fundamentally incompatible with the physical constraints of data centers. Surging enterprise demand and massive context windows have forced AI providers to introduce peak-hour usage rationing. In metropolitan hubs, the concentration of demand leads to significant rate-limiting during standard business hours (08:00–14:00 EST). In empirical observations of […]

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LoRA successfully specialized an LLM for high-variance speech, achieving significant WER improvements – but it wasn’t just the model. The results validated that building AI for widespread use requires a thoughtfully engineered data pipeline and careful dataset refinement, not simply massive amounts of data.

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You have alerts for everything. Uptime, latency, error rates. So why is nobody tracking whether a clinician can complete a workflow without opening a compensatory spreadsheet in a second tab? Medtech doesn’t have a UX problem. It has a measurement problem that everyone quietly agreed to call a UX problem — because a UX problem is someone else’s job to fix. I’ve spent eight years embedded in clinical products. The large ones, the specialised ones, the ones where […]

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Learning the underlying potential energy of stochastic gradient systems from partial and noisy observations is a fundamental problem arising in physics, chemistry, and data-driven modeling. Classical approaches often rely on direct regression of governing equations or velocity fields, which can be sensitive to noise and external perturbations and may fail when observations are incomplete. In this work, we propose a structure-aware, energy-based learning framework for inferring unknown potential functions in generalized diffusion processes, grounded in the energetic variational […]

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For years, undervolting has been the holy grail of laptop thermal management. It is the first thing any enthusiast does with a new machine. Fine-tune the voltage curve in MSI Afterburner, run a stress test, and enjoy lower temperatures and potentially higher boost clocks. I have been doing it for every laptop I have owned. But when I started running long, multi-hour Stable Diffusion sessions, I discovered a frustrating truth: undervolting is not enough. It is a fantastic […]

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Tech media did not collapse. It scaled. That may be the bigger story. Over the years, tech journalism became cleaner, faster, smarter, more organized, and more commercially efficient. The websites have improved. The headlines got sharper. The coverage became more structured. The business models got tighter. On the surface, that looks like progress. In many ways, it is. But something else happened at the same time. A lot of tech media stopped feeling like a living internet space […]

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