Frankfurt am Main, Germany, February 19th, 2026/CyberNewswire/–Link11 launches its new “AI Management Dashboard”, closing a critical gap in how companies manage AI traffic. Artificial intelligence is fundamentally changing internet traffic. But while many companies are already feeling the strain of AI crawlers on their infrastructures, they often lack clarity, reliable data, and operational control. With the new solution, the European IT security provider is, for the first time, making AI traffic transparent, controllable, and auditable within existing workflows. […]

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arXiv:2604.06202v1 Announce Type: new Abstract: Large language models (LLMs) have transformed natural language processing, yet their capabilities remain uneven across languages. Most multilingual models are trained primarily on high-resource languages, leaving many languages with large speaker populations underrepresented in both training data and evaluation benchmarks. This imbalance is particularly visible in the Turkic language family. This paper proposes a theoretical framework for studying cross-lingual transfer and parameter-efficient adaptation of multilingual LLMs within the Turkic language family, focusing on […]

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Five years ago, when I was thinking about the choice of my Master’s degree, I remember asking many people for advice. I was very grateful to my friends, as well as random people on LinkedIn and Reddit, who helped me make many important decisions. Fast forward to today. Having graduated from the university almost two years ago, I have pretty fresh and current experience of being a “young professional” in the tech industry. Now I am honoured to […]

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EFF has, for many years, raised the alarm about the proliferation of stalkerware—commercially-available apps designed to be installed covertly on another person’s device and exfiltrate data from that device without their knowledge. In particular, we have urged the makers of anti-virus products for Android phones to improve their detection of stalkerware and call it out explicitly to users when it is found. In 2020  and 2021, AV Comparatives ran tests to see how well the most popular anti-virus […]

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Architectural Paradigms and Market Consolidation in Production AI Systems The AI tooling landscape of 2026 represents a fascinating inflection point in the maturation of large language model (LLM) applications. What began as a Cambrian explosion of specialized tools has rapidly consolidated into distinct architectural patterns, each optimizing for specific computational trade-offs and user interaction paradigms. The Foundation Model Triumvirate: Diverging Optimization Strategies The dominance of ChatGPT, Claude, and Gemini isn’t merely about brand recognition — it reflects fundamentally different approaches to […]

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arXiv:2602.04795v2 Announce Type: replace-cross Abstract: Nonnegative matrix factorization (NMF) is a popular data embedding technique. Given a nonnegative data matrix $X$, it aims at finding two lower dimensional matrices, $W$ and $H$, such that $Xapprox WH$, where the factors $W$ and $H$ are constrained to be element-wise nonnegative. The factor $W$ serves as a basis for the columns of $X$. In order to obtain more interpretable and unique solutions, minimum-volume NMF (MinVol NMF) minimizes the volume of $W$. […]

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arXiv:2603.10022v1 Announce Type: new Abstract: This article summarizes the field of consumer protection law, from its historical roots to the contemporary challenges of the digital age. It outlines the legal doctrines governing consumer deception and unfair trade practices, highlighting the interplay between common-law, statutory, and private modes of regulation. The article then addresses the impact of artificial intelligence and big data on consumer markets, focusing on digital advertising and new forms of consumer fraud. Finally, it explores regulatory […]

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arXiv:2603.15674v2 Announce Type: cross Abstract: We present a complete theoretical characterization of Latent Posterior Factors (LPF), a principled framework for aggregating multiple heterogeneous evidence items in probabilistic prediction tasks. Multi-evidence reasoning arises pervasively in high-stakes domains including healthcare diagnosis, financial risk assessment, legal case analysis, and regulatory compliance, yet existing approaches either lack formal guarantees or fail to handle multi-evidence scenarios architecturally. LPF encodes each evidence item into a Gaussian latent posterior via a variational autoencoder, converting posteriors […]

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arXiv:2602.21428v1 Announce Type: new Abstract: Medical Vision Language Models (VLMs) can change their answers when clinicians rephrase the same question, which raises deployment risks. We introduce Paraphrase Sensitivity Failure (PSF)-Med, a benchmark of 19,748 chest Xray questions paired with about 92,000 meaningpreserving paraphrases across MIMIC-CXR and PadChest. Across six medical VLMs, we measure yes/no flips for the same image and find flip rates from 8% to 58%. However, low flip rate does not imply visual grounding: text-only baselines […]

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