Here's your daily roundup of the most relevant AI and ML news for August 13, 2026. We're also covering 7 research developments. Click through to read the full articles from our curated sources.
Research & Papers
1. BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents
arXiv:2511.20597v2 Announce Type: replace Abstract: The integration of artificial intelligence (AI) agents into web browsers introduces security challenges that go beyond traditional web application threat models. Prior work has identified prompt injection as a new attack vector for web agents, ...
Source: arXiv - Machine Learning | 10 hours ago
2. Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches
arXiv:2608.12007v1 Announce Type: new Abstract: Consumer reviews play an important role in shaping brand perception and business strategies, particularly in service-driven industries such as retail coffee. This study presents a comparative sentiment analysis framework for Starbucks customer revi...
Source: arXiv - Machine Learning | 10 hours ago
3. Adversarial Resilience of Poisson-Process Submodular Maximization over Matroids: From Robust Offline Optimization to Full-Bandit Learning
arXiv:2608.12134v1 Announce Type: new Abstract: We study nonnegative submodular maximization subject to a general matroid when the offline algorithm is given an arbitrary controlled value oracle. Our main result is an adversarial resilience theorem for the Spiteful Greedy Swap Poisson Process (S...
Source: arXiv - Machine Learning | 10 hours ago
4. An Efficient Near-Optimal Algorithm for Adversarial $m$-Set Bandits
arXiv:2608.12231v1 Announce Type: new Abstract: We study adversarial combinatorial bandits with $m$-set actions, where at each round the learner selects $m$ out of $d$ items and observes only the aggregate loss of the selected items. The resulting action set contains $K=\binom{d}{m}$ elements an...
Source: arXiv - Machine Learning | 10 hours ago
5. CoQui: A Coordinate-Conditioned Quantum Implicit Generative Adversarial Network for End-to-End Image Generation
arXiv:2608.11884v1 Announce Type: cross Abstract: Quantum generative adversarial networks (QGANs) have attracted increasing attention for image generation using parameterized quantum circuits. Existing amplitude-based approaches face two key limitations: pixel locations are typically encoded by ...
Source: arXiv - AI | 10 hours ago
6. Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control
arXiv:2608.12123v1 Announce Type: cross Abstract: LLM-agent services repeatedly execute small deterministic transitions between model and tool calls: route an outcome, update state, and emit the next effect. We ask when this control path exposes enough concurrent work for GPU execution, and what...
Source: arXiv - AI | 10 hours ago
7. Symbolic Machine Learning for Vapor-Liquid Equilibrium Prediction in Cx-N2 Binary Mixtures
arXiv:2608.11255v1 Announce Type: cross Abstract: Accurate prediction of vapor--liquid equilibrium (VLE) for hydrocarbon-nitrogen mixtures remains challenging for cubic equations of state, particularly across broad ranges of composition and hydrocarbon chain length. While deep learning models ca...
Source: arXiv - Machine Learning | 10 hours ago
Industry News
8. As AI safety concerns mount, three pioneers make the case for staying open
At Ai4, three of the world's most respected AI experts — Geoffrey Hinton, Fei-Fei Li, and Andrew Ng — debated regulation, open source access, and how America can compete as China advances in Asia.
Source: TechCrunch - AI | 20 hours ago
About This Digest
This digest is automatically curated from leading AI and tech news sources, filtered for relevance to AI security and the ML ecosystem. Stories are scored and ranked based on their relevance to model security, supply chain safety, and the broader AI landscape.
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