Here's your daily roundup of the most relevant AI and ML news for August 14, 2026. We're also covering 8 research developments. Click through to read the full articles from our curated sources.
Research & Papers
1. Do LLM Recommenders Know When They're Hallucinating? Auditing Confidence Calibration in Catalog Faithfulness
arXiv:2608.10008v2 Announce Type: replace-cross Abstract: LLM recommenders for top-K item suggestion regularly emit titles outside the target catalog. Prior audits report a binary out-of-domain rate; none ask whether the model knew. We jointly audit hallucination rate (OOD@10) and verbalized-con...
Source: arXiv - Machine Learning | 10 hours ago
2. GENADA: efficient generative time series adversarial attack framework
arXiv:2608.12535v1 Announce Type: new Abstract: Deep learning models are widely used for time series analysis in domains such as healthcare, finance, energy systems, and environmental monitoring. However, these models remain vulnerable to adversarial attacks, where small input perturbations caus...
Source: arXiv - Machine Learning | 10 hours ago
3. BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents
arXiv:2511.20597v2 Announce Type: replace-cross 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 ag...
Source: arXiv - AI | 10 hours ago
4. Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches
arXiv:2608.12007v1 Announce Type: cross 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 re...
Source: arXiv - AI | 10 hours ago
5. Large-scale Testing Global Optimization Methods with Black-box Adversarial Attacks
arXiv:2608.13296v1 Announce Type: new Abstract: Existing global optimization benchmark suites are of a moderate size and are based on a small number of analytical functions that date back even to the 1970s. This causes a risk of biasing the development of global optimization methods. We argue th...
Source: arXiv - Machine Learning | 10 hours ago
6. The Noise Premium in Adversarial Training for Kernel Regression
arXiv:2607.27995v2 Announce Type: replace-cross Abstract: Adversarial training can improve the robustness of predictive models to bounded perturbations, often at the cost of statistical efficiency. We study this trade-off in kernel regression over a reproducing kernel Hilbert space (RKHS). It is...
Source: arXiv - Machine Learning | 10 hours ago
7. 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
8. Adversarial Resilience of Poisson-Process Submodular Maximization over Matroids: From Robust Offline Optimization to Full-Bandit Learning
arXiv:2608.12134v1 Announce Type: cross 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 ...
Source: arXiv - AI | 10 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.
Want to see how your favorite models score on security? Check our model dashboard for trust scores on the top 500 HuggingFace models.