Vega: Zero-knowledge proofs for digital identity in the age of AI
Vega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps.
The post Vega: Zero-knowledge proofs for digital identity in the age of AI appeared first on Microsoft Research.
MagBridge-Battery: A Synthetic Bridge Dataset for Li-ion Magnetometry and State-of-Health Diagnostics
arXiv:2605.20240v1 Announce Type: new
Abstract: Battery health diagnostics today rely overwhelmingly on electrochemical signals measured at the cell terminals. A parallel literature has shown that magnetic sensing can resolve information that terminal-only measurements miss, but method development ...
OSCToM: RL-Guided Adversarial Generation for High-Order Theory of Mind
arXiv:2605.20423v1 Announce Type: new
Abstract: Large Language Models (LLMs) perform well on many language tasks, but their Theory of Mind (ToM) reasoning is still uneven in complex social settings. Existing benchmarks, including ExploreToM, do not always test the recursive beliefs and information ...
arXiv:2605.20467v1 Announce Type: new
Abstract: Neural networks can be trained to rank the choices made by logical reasoners, resulting in more efficient searches for answers. A key step in this process is creating useful embeddings, i.e., numeric representations of logical statements. This paper i...
AI agents keep breaking in production. Here's why nobody's fixed it yet
78% of enterprises have an AI agent pilot running. Only 14% have successfully scaled one. The gap isn't a model problem. It's an engineering one (and it's hiding in plain sight....)
Forget electrons, this breakthrough uses light-matter particles to power AI
Researchers at Penn have created a hybrid light-matter particle that could dramatically speed up AI computing while using far less energy. The breakthrough may help replace some electronic computing processes with ultra-efficient light-based technology.
SkillSmith: Compiling Agent Skills into Boundary-Guided Runtime Interfaces
arXiv:2605.15215v1 Announce Type: new
Abstract: Recently, skills have been widely adopted in large language model (LLM)-based agent systems across various domains. In existing frameworks, skills are typically injected into the agent reasoning loop as contextual guidance once matched to a runtime ta...
NASA’s new AI space chip could let spacecraft think for themselves
NASA is testing a next-generation space computer chip that could give spacecraft the ability to operate far more independently in deep space. The radiation-hardened processor is showing performance levels hundreds of times beyond current spaceflight computers while surviving punishing tests designed...
Vision-Based Runtime Monitoring under Varying Specifications using Semantic Latent Representations
arXiv:2605.13923v1 Announce Type: new
Abstract: We study certified runtime monitoring of past-time signal temporal logic (ptSTL) from visual observations under partial observability. The monitor must infer safety-relevant quantities from images and provide finite-sample guarantees, while being \emp...
Your data engineers may be more influential than you think
The data engineer has gone from a largely behind-the-scenes role to one of the most strategically important positions in a modern technology organization. The leaders who understand why are making significantly better infrastructure decisions than the ones who do not.
Think Twice, Act Once: Verifier-Guided Action Selection For Embodied Agents
arXiv:2605.12620v1 Announce Type: new
Abstract: Building generalist embodied agents capable of solving complex real-world tasks remains a fundamental challenge in AI. Multimodal Large Language Models (MLLMs) have significantly advanced the reasoning capabilities of such agents through strong vision...
CAWI: Copula-Aligned Weight Initialization for Randomized Neural Networks
arXiv:2605.12580v1 Announce Type: new
Abstract: Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing randomly initialized input-to-hidden weights, which permits a closed-form solution for the output layer. However, conventional random initialization is blin...
Towards Robust Federated Multimodal Graph Learning under Modality Heterogeneity
arXiv:2605.12584v1 Announce Type: new
Abstract: Recently, multimodal graph learning (MGL) has garnered significant attention for integrating diverse modality information and structured context to support various network applications. However, real-world graphs are often isolated due to data-sharing...
The future AI team: What enterprise AI organizations may look like by 2030
Ask most enterprises what their AI team looks like in 2030 and you will get a blank stare followed by a reference to their current headcount.
That is understandable. It is also a problem. Because the AI team of 2030 is going to look very little like the AI team of today...
New quantum algorithm solves “impossible” materials problem in seconds
A new quantum-inspired algorithm has cracked a problem so massive that conventional supercomputers struggle to even approach it. Researchers used the method to simulate extraordinarily complex quantum materials known as quasicrystals, opening the door to powerful new quantum devices and ultra-effici...
Your “um” and pauses could reveal early dementia risk
The little pauses, “ums,” and moments when you struggle to find the right word may reveal far more about your brain than anyone realized. Researchers discovered that everyday speech patterns are closely tied to executive function — the mental system that powers memory, planning, focus, and flexible ...
Interpretable EEG Microstate Discovery via Variational Deep Embedding: A Systematic Architecture Search with Multi-Quadrant Evaluation
arXiv:2605.10947v1 Announce Type: new
Abstract: EEG microstate analysis segments continuous brain electrical activity into brief, quasi-stable topographic configurations that reflect discrete functional brain states. Conventional approaches such as Modified K-Means operate directly in electrode spa...