Security Correspondent
Nadia Vale covers security failures, system safeguards and the difficult business of establishing trust. Her beat connects technical disclosures with their consequences for users and institutions. She favors specific threat models over sweeping claims that a system is safe or unsafe.
1,019 published articles · Showing 1–20
Standard planners built on visual world models typically evaluate predicted trajectories against a fixed end-state image, a strategy that can stall control when optimal paths temporarily move away from the target Aim Short to Reach Far: Your Frozen World Model Can Plan Better…...
Read article →The lab says it cannot notify the people affected, because its privacy design prevents it from linking the images back to the accounts that supplied them....
Read article →The landscape of artificial intelligence is marked by parallel trajectories of groundbreaking innovation and persistent vulnerability. Recent research reveals significant progress in direct neural-to-text translation, simultaneously with the quantification of near-verbatim data e...
Read article →A new research paper from arXiv CS. AI reveals the rapid emergence of AI agent platforms, hosting over 167,000 agents that demonstrate self-organizing, peer-to-peer interaction, and independent learning behaviors without direct researcher intervention arXiv CS....
Read article →Recent research unveils a significant leap in AI's capacity for computer vision and 3D scene understanding, enabling systems to reconstruct complex environments and identify objects with enhanced efficiency from minimal data inputs. This development, detailed across new papers fr...
Read article →New research published on arXiv CS. AI on 2026-04-14 highlights a critical juncture in generative AI, simultaneously advancing synthetic content creation while grappling with persistent issues of reliability and the escalating challenge of attribution....
Read article →New research published on arXiv CS. LG reveals a critical vulnerability in current AI methodologies for modeling complex systems: these architectures may fail to internalize governing physical laws or accurately reflect internal system organization, potentially exposing novel att...
Read article →The latest research from arXiv CS. LG reveals a simultaneous surge in attempts to deploy artificial intelligence into mission-critical domains, coupled with a stark exposition of the deep-seated challenges preventing reliable and secure integration....
Read article →Recent rigorous analyses reveal significant limitations in current Artificial Intelligence models applied to critical scientific domains, challenging their perceived reliability. These systems, frequently deployed to accelerate complex discovery processes, consistently fail to de...
Read article →New research from arXiv CS. LG, published on May 28, 2026, illuminates fundamental challenges in designing adaptive learning systems, particularly concerning network interference and the opaque mechanisms of exploration-exploitation strategies arXiv CS....
Read article →A significant security lapse by prison payphone service Pay Tel has publicly exposed the driver's licenses and sensitive communications of over 300,000 callers, underscoring systemic failures in data handling for vulnerable populations. Simultaneously, a new phishing campaign tar...
Read article →New research published today on arXiv CS. LG reveals a critical acceleration in the AI arms race, exposing sophisticated adversarial machine learning techniques and fundamental limits in current defensive postures....
Read article →Four new research preprints on arXiv detail advanced memory mechanisms and continual learning strategies for artificial intelligence, aiming to address critical issues such as catastrophic forgetting in generative models and computational bottlenecks in large language models (LLM...
Read article →New research released on arXiv details a concerted push toward autonomous AI systems for real-time data analysis and insight generation across critical sectors. While these advancements promise to overcome the limitations of reactive analytics, the same research implicitly expose...
Read article →Multiple significant papers in machine learning theory have been updated on arXiv CS. LG today, reflecting ongoing, iterative refinements across critical domains including Bayesian optimization, classifier boundary analysis, and out-of-distribution detection....
Read article →The digital landscape is shifting, with new research unveiled on arXiv CS. AI underscoring a rapid acceleration in generative AI capabilities....
Read article →Multimodal Large Language Models (MLLMs) are exhibiting critical hallucination behaviors and inherent limitations in intent comprehension, introducing significant operational risks across agricultural and embodied AI applications. Recent research highlights that these models, des...
Read article →A recent wave of research papers, published concurrently on arXiv CS. AI, exposes a deeply entrenched landscape of vulnerabilities within Large Language Models (LLMs), ranging from fundamental safety mechanism bypasses to profound ethical concerns regarding their operational depl...
Read article →The architecture underpinning Large Language Models (LLMs) is revealing fundamental limitations and exploitable biases, according to a surge of new research published on arXiv CS. LG....
Read article →Recent research emerging from arXiv, published on May 28, 2026, details significant architectural and inference optimizations for large language models (LLMs). These papers collectively target critical operational weaknesses: the exorbitant computational cost of deployment, the l...
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