The record
Published reporting, analysis and commentary from the Automatica newsroom.
A significant cluster of new research, published on arXiv CS. LG on May 20, 2026, reveals a concerted scientific effort to refine the foundational architectures and training methodologies of artificial intelligence.
Today, new research published on arXiv CS. AI reveals significant strides in Large Language Model (LLM) agents, showcasing capabilities that promise to make our digital and physical environments more reliable and our interactions with AI more helpful and secure.
The proliferation of artificial intelligence across critical infrastructure and societal functions has brought into sharp focus the imperative of robust AI security. A recent surge of research, published primarily on arXiv CS.
Another day, another torrent of academic papers attempting to patch the increasingly complex, perpetually underperforming edifice that is the Large Language Model. Today, arXiv CS.
The conventional wisdom in AI has long been 'bigger is better,' but a flurry of new research from arXiv, published today, signals a refreshing pivot towards efficiency. Engineers are finding ingenious ways to extract more performance from less, directly tackling the formidable co
For years, the AI world has been telling us how smart its digital brains are by pointing to leaderboards and aggregate scores. Turns out, those 'metrics' are about as useful as judging a gourmet chef by how well they microwave a Hot Pocket.
New artificial intelligence frameworks are significantly enhancing capabilities in financial crime detection and continuous health monitoring, with recent academic research outlining systems designed to identify complex interbank fraud, cross-industry money laundering schemes, an
The landscape of artificial intelligence research has exhibited a significant expansion today, with the simultaneous publication of multiple pre-print studies on arXiv CS. AI.
New research published today on arXiv details significant advancements in AI's capacity to accelerate scientific and engineering simulations, promising orders-of-magnitude efficiency gains across industries arXiv CS. AI.
A fresh wave of foundational AI research has just landed on arXiv, offering crucial insights into the intricate mechanisms governing advanced AI systems. These papers, published on May 20, 2026, collectively challenge prevailing assumptions, from how AI agents explore uncertain e
The veil between our private selves and the hungry gaze of algorithmic systems is thinning, dissolving under the relentless advance of new artificial intelligence research. Today, a flurry of papers released on arXiv CS.
Recent research, published on May 20, 2026, unveils significant advancements in enhancing the reasoning capabilities of Large Language Models (LLMs) while simultaneously diagnosing and mitigating critical operational failure modes. These developments are poised to address long-st
A torrent of cutting-edge AI research, published today on arXiv, is fundamentally reshaping our understanding of Large Language Model (LLM) agents, pushing them beyond experimental curiosities into a new era of robust, production-ready systems. These papers, all released on May 2
OpenAI has formalized a multi-year AI partnership in Singapore, a move designed to expand the deployment of artificial intelligence, cultivate local talent, and provide support for businesses and public services within the region OpenAI Blog. This strategic initiative signifies a
The confluence of recent academic publications from arXiv, largely published on May 19, 2026, signals a pivotal moment in the advancement of AI for computer vision and robotics, moving these technologies closer to ubiquitous real-world deployment. This surge in research not only
A new frontier is being drawn, not on maps of the physical world, but within the very microscopic landscape of our bodies. Research emerging from arXiv reveals that artificial intelligence is rapidly colonizing nanomedicine, focusing its formidable gaze on property prediction and
Hold the champagne, folks, because a new research paper just dropped on arXiv arXiv CS. AI!
New research published on arXiv reveals significant advancements in artificial intelligence models' ability to emulate human visual perception and enhance text-to-image generation. These developments, detailed in preprints from May 19, 2026, fundamentally expand the attack surfac
The consistent influx of academic contributions on arXiv CS. AI, with a substantial release on May 19, 2026, signals an intensified focus within the research community on the fundamental challenges governing the reliable and efficient deployment of Large Language Models (LLMs) an
The discovery of a "safety geometry collapse" in multimodal large language models (MLLMs) highlights a critical, often overlooked challenge: the failure of MLLMs to consistently transfer safety capabilities from text to semantically equivalent non-text inputs arXiv:2605. 18104.