In this article, you will learn how agentic AI architecture has evolved by mid-2026, including the shift away from orchestrated reasoning loops, the rise of...
A hands-on guide to tracking experiments, logging models, and reproducing results with ML Flow.
The post Are Your ML Experiments a Mess? Here’s the Fix appeared first on Towards Data Science.
Meta Open-Sources Astryx: An Agent-Ready React Design System With 150+ Accessible Components, Seven Themes, and a CLI
Meta has open-sourced Astryx, the React and StyleX design system it ran internally for eight years across 13,000+ apps. It ships 150+ accessible components, seven themes, dark mode, templates, and an agent-ready CLI under MIT — with React 19+ required.
The post Meta Open-Sources Astryx: An Agent-Rea...
NVIDIA Releases Cosmos 3 Edge: A 4B-Parameter Open World Model That Reasons and Generates Robot Actions On-Device
NVIDIA has released Cosmos 3 Edge, a 4-billion-parameter open world model built to run on-device. It helps robots and vision AI agents understand surroundings, reason in real time, and generate robot actions locally. The Cosmos 3 family included Cosmos 3 Nano (16B) and Cosmos 3 Super (64B) shipped o...
OpenAI and Hugging Face partner to address security incident during model evaluation
OpenAI and Hugging Face share early findings from a security incident during AI model evaluation, highlighting advanced cyber capabilities and lessons for defenders.
DocOCR-Eval: A Correction-Based Framework for OCR Tool Selection Without Ground Truth
arXiv:2607.16203v1 Announce Type: new
Abstract: Document parsing is a foundational step for document understanding tasks such as visual question answering and key information extraction, as it transforms unstructured scanned images into structured representations by extracting textual, visual, and ...
Fully-sensorized smart-eyewear platform for on-device Machine Learning
arXiv:2607.16222v1 Announce Type: new
Abstract: This paper presents ARGO, a smart eyewear platform designed to bridge ergonomic comfort, high computational throughput, and energy efficiency. Unlike cloud-dependent solutions, ARGO leverages the STM32N6 microcontroller and its integrated Neural Proce...
LLM Unlearning for Cyber Defense: A Survey on Methods, Challenges, and Emerging Threats
arXiv:2607.16227v1 Announce Type: new
Abstract: LLMs are increasingly deployed in security-critical systems across healthcare, finance, education, and decision support, yet their inability to forget creates serious cybersecurity, privacy, and safety risks. Sensitive personal information, copyrighte...
Rater State Bias in RLHF Preference Data: An Audit Framework
arXiv:2607.16195v1 Announce Type: new
Abstract: We identify a structured confound in Reinforcement Learning from Human Feedback (RLHF). Pairwise preference labels are intended to reflect the compared outputs, but they may also reflect the rater's state during annotation. Under sustained stressful o...
Design and Validation of a Lightweight 1D CNN for Affective Touch Classification in Soft Plush Companions
arXiv:2607.16196v1 Announce Type: new
Abstract: Soft, sensorized companions offer a physically safe and emotionally intuitive interface for socially assistive technologies, yet their deformability and multichannel tactile sensing complicate the robust interpretation of human affect. This study pres...
Some Large Language Models Exhibit Consistent Risk Attitudes
arXiv:2607.16197v1 Announce Type: new
Abstract: As artificial intelligence systems are deployed in open-ended, high-stakes settings, a critical dimension remains unmeasured: how perceived risk is translated into action. We test whether large language models (LLMs) exhibit systematic and consistent ...
PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection
arXiv:2607.16199v1 Announce Type: new
Abstract: Multi-agent LLM systems increasingly rely on a Planner to decompose goals into sub-task sequences that downstream Executor and Critic agents execute and audit. We identify the planning phase as a critical attack surface: a single injection into the Pl...
Environment-free Synthetic Data Generation for API-Calling Agents
Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale typically requires fully implemented environments with executable APIs and realistic, pre-populated backend databases, creating a major bottleneck for s...
Accelerating Text-to-Video Generation with Calibrated Sparse Attention
Recent diffusion models enable high-quality video generation, but suffer from slow runtimes. The large transformer-based backbones used in these models are bottlenecked by spatiotemporal attention. In this paper, we identify that a significant fraction of token-to-token connections consistently yiel...
Alibaba’s Tongyi Lab Releases Qwen-Audio-3.0-TTS, a Hosted Text-to-Speech Model in Flash and Plus Tiers Across 16 Languages
Alibaba’s Tongyi Lab has released Qwen-Audio-3.0-TTS, a production-oriented text-to-speech (TTS) system. The model ships in two variants from the same lineage. Flash targets real-time interaction. Plus targets high-quality generation. Both are delivered as hosted models through Alibaba Cloud Model S...
AI’s most important protocol is getting a little bit easier to use
The Model Context Protocol (MCP) is one of the basic building blocks of AI interoperability, giving AI models a secure way to access external data sources and services. It’s the plumbing that lets a chatbot reach into your calendar, your database, or your internal tools, instead of engineers buildin...