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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 Bayesian Inference and Decision Audits Reveal Unreliability in Frontier AI Evaluation Archives Dali casualty exposes erosion of technical ownership in shipmanagement, warns veteran Kapoor 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 Bayesian Inference and Decision Audits Reveal Unreliability in Frontier AI Evaluation Archives Dali casualty exposes erosion of technical ownership in shipmanagement, warns veteran Kapoor

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LLM-Encoded Knowledge Guides Federated Graph Recommendation to Improve Accuracy

Artificial Intelligence #federated learning#graph recommendation

LLM-Encoded Knowledge Guides Federated Graph Recommendation to Improve Accuracy

Researchers propose a federated graph recommendation framework that leverages LLM-encoded semantic knowledge to guide cross-client structural aggregation, addressing the challenge of non-IID client data. The method consistently outperforms existing federated graph baselines on standard benchmarks.

Jun 16, 2026 1 source