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DYNA Framework Uses Temporal Knowledge Graphs to Reduce LLM Forgetting Without Retraining RAMS: Resource-Adaptive Model Switching for Embedded Edge Perception Under Load Open-SWE-Traces: 207K Multilingual Trajectories Set New Standard for Autonomous Software Engineering Agents Infant-Inspired Noise Boosts Deep RL Exploration, Research from arXiv Shows Mutual Distillation of Dual Foundation Models Achieves State-of-the-Art PET/CT Segmentation with Only 5 Labeled Cases SPARK Method Activates Latent Security Knowledge in LLMs for Secure Code Generation Apple explains why Siri AI took so long: first version ready last year but rebuilt from ground up New LLM Framework Detects Phishing Emails with Over 90% Accuracy Dual-Granularity Orthogonal Disentanglement: New Framework Boosts Generalizable Audio Deepfake Detection Medical Image Segmentation Survey: U-Net, Transformers, SAM and Clinical Translation Challenges DYNA Framework Uses Temporal Knowledge Graphs to Reduce LLM Forgetting Without Retraining RAMS: Resource-Adaptive Model Switching for Embedded Edge Perception Under Load Open-SWE-Traces: 207K Multilingual Trajectories Set New Standard for Autonomous Software Engineering Agents Infant-Inspired Noise Boosts Deep RL Exploration, Research from arXiv Shows Mutual Distillation of Dual Foundation Models Achieves State-of-the-Art PET/CT Segmentation with Only 5 Labeled Cases SPARK Method Activates Latent Security Knowledge in LLMs for Secure Code Generation Apple explains why Siri AI took so long: first version ready last year but rebuilt from ground up New LLM Framework Detects Phishing Emails with Over 90% Accuracy Dual-Granularity Orthogonal Disentanglement: New Framework Boosts Generalizable Audio Deepfake Detection Medical Image Segmentation Survey: U-Net, Transformers, SAM and Clinical Translation Challenges
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New LLM Framework Detects Phishing Emails with Over 90% Accuracy Technology
Artificial Intelligence #phishing#email

New LLM Framework Detects Phishing Emails with Over 90% Accuracy

A paper on arXiv introduces LLMPEA, a framework using GPT-4o, Claude Sonnet 4, and Grok-3 to detect phishing emails with over 90% accuracy. The study also reveals vulnerabilities to adversarial attacks, prompt injection, and multilingual attacks, emphasizing the need for hardening before deployment.

Jun 16, 2026 1 source
Dual-Granularity Orthogonal Disentanglement: New Framework Boosts Generalizable Audio Deepfake Detection Technology
Artificial Intelligence #audio deepfake detection#disentanglement

Dual-Granularity Orthogonal Disentanglement: New Framework Boosts Generalizable Audio Deepfake Detection

A new paper on arXiv proposes a dual-granularity orthogonal disentanglement framework for generalizable audio deepfake detection. The method enforces sample-level cosine orthogonality and batch-level cross-covariance regularization to avoid speaker identity leakage. Experiments show equal error rates of 1.35%, 7.88%, and 21.58% on standard benchmarks.

Jun 16, 2026 1 source
AI and Deep Learning Transform Cattle Identification for Livestock Supply Chain Security Technology
Artificial Intelligence #machine learning#deep learning

AI and Deep Learning Transform Cattle Identification for Livestock Supply Chain Security

A systematic review of machine learning and deep learning techniques for cattle identification reveals that deep learning methods like CNNs, ResNets, and YOLO outperform classical approaches in detection and recognition tasks. Key features include muzzle prints and coat patterns, while challenges remain in dataset availability and real-time processing.

Jun 16, 2026 1 source