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RAG and LLMs Combined to Generate Personalized Reading Content at Desired Complexity Unassigned Agents in Multi-Agent Path Finding Addressed by Compilation-Based Solvers New Framework Reduces Visual Hallucinations in Multimodal AI Systems Without Retraining MAF Framework Dynamically Optimizes Prompting for Multimodal Sentiment Analysis Study on Pedestrian Attribute Recognition Identifies Sparsity Wall and Optimizes Edge Deployment AI Framework Targets 50% Water Loss in Jordan with LLM and Digital Twin Integration AnonShield: Scalable On-Premise Pseudonymization Cuts Vulnerability Data Processing from 92 Hours to Under 10 Minutes MoFore: A New Self-Supervised Framework Learns Video Representations by Forecasting Future Latent Embeddings Do LLMs Reliably Identify Correct Information Units in Aphasic Discourse? A New Study Evaluates Four Models AI Video Generation Method for Cardiac MRI Addresses Data Scarcity with Latent Motion Modeling RAG and LLMs Combined to Generate Personalized Reading Content at Desired Complexity Unassigned Agents in Multi-Agent Path Finding Addressed by Compilation-Based Solvers New Framework Reduces Visual Hallucinations in Multimodal AI Systems Without Retraining MAF Framework Dynamically Optimizes Prompting for Multimodal Sentiment Analysis Study on Pedestrian Attribute Recognition Identifies Sparsity Wall and Optimizes Edge Deployment AI Framework Targets 50% Water Loss in Jordan with LLM and Digital Twin Integration AnonShield: Scalable On-Premise Pseudonymization Cuts Vulnerability Data Processing from 92 Hours to Under 10 Minutes MoFore: A New Self-Supervised Framework Learns Video Representations by Forecasting Future Latent Embeddings Do LLMs Reliably Identify Correct Information Units in Aphasic Discourse? A New Study Evaluates Four Models AI Video Generation Method for Cardiac MRI Addresses Data Scarcity with Latent Motion Modeling

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autonomous agents

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Your Agent Has a Genome: New Framework Analyzes LLM Agent Behavior to Enable Runtime Governance

Artificial Intelligence #llms#autonomous agents

Your Agent Has a Genome: New Framework Analyzes LLM Agent Behavior to Enable Runtime Governance

Researchers propose Base Sequence Analysis, a framework that encodes runtime behavior of LLM-powered autonomous agents into symbolic sequences (X, E, P, V). Analyzing 347 execution traces revealed key patterns: the trigram P-X-P lowered success rate by 10.4%, and verification transition E->V occurred only 2.1% of the time. They designed Governor, a three-layer runtime intervention system that increased task success by 6.2% and reduced token consumption by 44% in a production ReAct agent system.

Jun 16, 2026 1 source

New Survey Maps Agentic Security: Applications, Threats, and Defenses for Autonomous AI

Artificial Intelligence #agentic security#ai security

New Survey Maps Agentic Security: Applications, Threats, and Defenses for Autonomous AI

A new survey from arXiv provides the first holistic overview of agentic security, covering how LLM-based agents are used in cybersecurity, their vulnerabilities, and countermeasures. The analysis of over 260 papers reveals that agentic systems are structurally fragile and require defenses spanning the full agent lifecycle.

Jun 16, 2026 1 source