XGBoost hits 98.62% malware detection accuracy in new preprint
XGBoost outperformed neural networks and SVM in a malware detection benchmark, but the 98.62% figure is self-reported and unverified.
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XGBoost outperformed neural networks and SVM in a malware detection benchmark, but the 98.62% figure is self-reported and unverified.
AntiSkillBench tests 7,500 dialogue traces across three frontier agents and finds privacy risks persist from explicit data to communication style.
TrainShield, a new arXiv preprint, proposes AI cybersecurity training embedded in browsing workflows when phishing or data-loss risks are detected.
An August 2026 arXiv preprint claims 98% accuracy detecting AI text from GPT, LLaMA and Claude, with token-level explanations for auditors.
Circles used OpenAI's API and Codex to personalise telecom services, self-reporting a 22% ARPU lift and 9% churn cut. What's verified and what isn't.
An arXiv preprint proposes replaying temporally-evolving enterprise worlds to test AI agents at any moment, fixing a blind spot in current evals.
New arXiv paper proposes SkillBoost, a three-stage framework that stops LLM agents overfitting to limited experience and forgetting solved tasks.
EvoPINN uses an LLM agent to automatically discover and validate algorithms for physics-informed neural networks, replacing manual tuning.
TAPR uses reinforcement learning to turn vague user prompts into task-optimized instructions, lifting accuracy on Natural Questions and GSM8K benchmarks.
AI-generated research papers scored below the midpoint in the first automated multi-model peer review, and one AI reviewer disagreed with the others
GLASS, a new arXiv preprint, uses sparse autoencoders to extract a user's writing style and inject it at inference, no fine-tuning or retrieval needed.
An arXiv preprint shows organizations can collaboratively predict equipment failure using federated survival analysis without sharing raw sensor data.