KV-PRM is an efficient process reward model that eliminates text re-encoding by directly using the KV cache from LLM generation, reducing scoring cost from O(L²) to O(L). It matches or outperforms text-PRMs on benchmarks with up to 5000x FLOPs reduction, 37x latency reduction, and 34x memory reduction.

MedRealMM is a large-scale benchmark built from de-identified patient-doctor interactions from a nationwide Chinese internet hospital. It includes 5,620 multimodal cases across 64 departments and uses a Multimodal Clinical Challenge Point (MCCP) extraction framework to create standardized next-response generation tasks. Evaluation of 19 LLMs shows that image information is critical for reliable clinical performance, and current frontier models, while meeting positive clinical criteria comparably to physicians, trigger more negative criteria, highlighting safety-sensitive error avoidance as a key bottleneck.

The L-MAD framework systematically evaluates multi-agent debate structures and aggregation methods in Legal Textual Entailment. By assigning expert personas, it improves upon single-agent baselines by up to 8%. Increasing agent population reduces inconsistency and improves accuracy, but extending discussion rounds induces over-deliberation drift where agents reinforce each other's mistakes. The findings outline practical boundaries for deploying multi-agent systems in high-stakes legal reasoning.

This paper introduces a neuro-agentic control framework that couples an LLM planner with a time-series foundation model (TimesFM) using counterfactual physics injection to ensure physics-grounded autonomous defense, outperforming LSTM and TCN on SWaT dataset with zero hallucinated actions.

ARCANA is a collaborative multi-agent framework for solving ARC-AGI-2 tasks under strict test-time and hardware constraints. It decomposes each task into iterative perception, hypothesis generation, symbolic execution, and reflective refinement. Using a differentiable blackboard and learned meta-controller, it combines structured program search with adaptive multi-turn correction, improving reasoning efficiency and solution quality on abstract transformation tasks.

Researchers frame the formalization of the Vlasov equation's mean-field derivation as a strategy game, where a mathematician directs an AI system to convert LaTeX documents into Lean 4 proof assistant code. The case study successfully completes a full formalization of well-posedness for the nonlinear Vlasov equation via Dobrushin's mean-field route, including existence, uniqueness, stability estimate, and mean-field limit, as well as a short-time superposition principle. About one-sixth of the formalization yields a self-contained layer reusable by the broader library.

Long-Horizon-Terminal-Bench is a terminal benchmark of 46 long-horizon tasks across nine categories, including experiment reproduction, software engineering, multimodal analysis, interactive games, and scientific computing. It decomposes tasks into fine-grained subtasks to provide dense intermediate rewards and partial credit, offering a more complete evaluation of AI agents. Evaluating 15 frontier models, the strongest achieved a 15.2% pass@1 at a partial-reward threshold of 0.95 and 10.9% at a perfect-reward threshold of 1.0, with mean pass rates of 4.3% and 1.7% respectively, indicating significant room for improvement.

GATS is a new agent planning framework that uses systematic UCB1-based tree search and a layered world model to eliminate LLM calls during planning, achieving 100% success rate. It outperforms LATS and ReAct on synthetic tasks and 12 challenging scenarios with lower computational cost.

A new study challenges the notion that LLM reliability stems solely from model capability, showing that inference-time control plays a key role. The CogniConsole architecture externalizes this control into a structured interface that combines programmatic coordination with bounded prompt-based reasoning. Experiments with 489 probes demonstrate that increasing structural scaffolding systematically reduces output variance and failure rates, suggesting many failures are due to under-specified control.

This paper presents a theoretical framework for adversarial robustness by reducing it to a lattice traversal problem. It introduces sound and complete interval certifications for MLPs, develops lattice traversal operators, and reveals asymmetries in optimization complexity, with polynomial-time algorithms for complete certifications and strong intractability for sound certifications.

Researchers from MIT and Thorn have developed an auditing technique that detects whether generative AI models can produce child sexual abuse material (CSAM) by analyzing internal model adaptations, without generating any outputs. The method achieved 100% accuracy in tests and is scalable, offering a practical tool for platforms and law enforcement.

The Global Careers Hub provides free AI tools, scholarships, and career resources to help users plan their careers.

AVA is an open-source, self-hosted voice AI agent for Asterisk/FreePBX, offering quick deployment, multi-agent management, real-time dashboard, and support for multiple AI engines. Recent updates include stability fixes, silence watchdog, and per-agent voice selection.

31-year-old voice actor Shen Anyu faces a career crisis due to AI clones of his voice. The clones spread widely, causing platforms to flag his real recordings as synthetic, impacting his income. He and his wife spend significant time tracking infringements, but enforcement is difficult. AI voice cloning tools are disrupting China's short drama, audiobook, and short video industries, with many voice actors facing similar challenges and declining earnings.

The author shares his perspective on artificial intelligence, placing himself in the high-impact, medium-high positive quadrant. He addresses questions about job displacement, the future of SaaS, pricing changes, and capital expenditure, arguing that AI will streamline processes and reshape business models without causing undue alarm.

Baton is a macOS menu bar utility that monitors AI coding agents like Claude Code and Codex, displaying a live count of sessions waiting for your attention. It uses FSEvents for instant updates and allows click-to-jump to specific sessions.

Senior China correspondent Amy Hawkins on China’s embrace of AI, from medical avatars to food delivery drones and state surveillance. While the spread of AI has been met with skepticism in the West, China has fully embraced the technology, with millions using AI doctors, intelligent robots in factories, and drones delivering food on the Great Wall. The state has also eagerly adopted AI for surveillance.

Tinier is a free set of browser-based media tools for compressing, converting, and upscaling images, as well as converting video to GIF, all without uploading files to any server.

Christopher Nolan dismisses AI fears as 'nonsense', says his big-budget location-shot films will survive, and calls criticism of Lupita Nyong'o 'irrelevant'.

Clark is a solo-built AI assistant aiming to match Manus agent in features and capabilities. It can use the computer, browser, perform deep research, and integrate with Google tools. Thousands use it daily.

NeuroVFM is a generalist neuroimaging foundation model from the University of Michigan, trained on 5.24M clinical MRI and CT volumes. Its Vol-JEPA base extends I-JEPA and V-JEPA to volumetric medical imaging, learning brain anatomy and pathology without radiology-report labels.

A toy dynamical model of whether the AI workforce that builds future AI ends up cooperative or uncooperative: where the basin boundary lies, what current evidence says about which side we are on, and what would tell us we are on the good path.

The concept of Directly Responsible Individuals (DRI) originated at Apple and is defined as the person ultimately accountable for a project's success or failure. The author argues that LLM-powered agents should never be considered DRIs because only humans can take accountability. This echoes IBM's 1979 training slide stating that a computer cannot be held accountable and therefore must never make a management decision.

This article argues that AI's true potential lies in democratizing access to expertise, not just boosting productivity. Studies show AI can narrow educational gaps, but only when designed as a tutor rather than an answer machine.

OneDev integrates AI users as virtual teammates that work from issues, create pull requests, review code, and respond to CI/CD failures, keeping all work visible and traceable within the same platform.

Lyzr, a three-year-old Jersey City startup that helps enterprises build AI agents, used its own AI agent SivaClaw to raise a $100 million Series B at a roughly $500 million valuation. The system fielded questions from over 130 investors, drafted investment memos, and tracked which slides backers lingered on, proving the product works.

After three months of AI-assisted development, productivity has soared, but mental exhaustion has emerged from the shift to constant high-level design decisions. The article explores how AI changes cognitive load, creating decision fatigue, architectural flatness, review blind spots, and the need for new adaptation strategies.

An Argo CD UI extension that adds an AI-powered assistant tab, allowing users to query Kubernetes resources in natural language with context including manifest, events, and optional logs. Compatible with any OpenAI-compatible backend and requires Argo CD v2.13+.

Recent benchmark results show GPT-5.6 Sol achieves 100% recall and a 0.91 F1 score at $0.70 per PR review, outperforming all Anthropic models. No Anthropic model reaches the frontier; Fable 5 is dominated by cheaper alternatives. Grok 4.5 and Gemini 3.1 Flash Lite offer cost-effective options. The study uses private synthetic repos to prevent contamination.

xysq.ai is a collaborative memory platform for AI-native teams and enterprises. It connects AI tools and apps, captures context from team workflows, builds a living knowledge graph, and provides the right context when agents need it. Features include isolated team vaults, role-based access, document organization, and a strict no-training-on-user-data privacy policy.