Agent Systems

Move beyond simple text generation and step into the era of autonomous AI. This category covers Agentic Systems and AI Agents that can plan, reason, and interact with digital environments 🌐. Explore cutting-edge research on hierarchical control, reinforcement learning, and multi-agent frameworks that are teaching AI to navigate software, use apps, and solve multi-step problems just like a human.

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents

Leave a Comment / Agent Systems, Machine Learning /

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents | AI Trend Blend AITrendBlend Machine Learning Computer Vision Agent Systems About Deep Reinforcement Learning · Journal of Machine Learning Research 26 (2025) 1–40 · 22 min read When Memory Actually Matters: How Memory Gym’s Endless Tasks Expose What Benchmarks Have Been Missing All Along […]

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Best AI Agents for Small Business in 2026: Tools That Act as Virtual Employees.

Best AI Agents for Small Business in 2026: Tools That Act as Virtual Employees

Leave a Comment / Agent Systems, Prompt Engineering, Tech News /

Best AI Agents for Small Business in 2026: Tools That Act as Virtual Employees aitrendblend Prompts Claude ChatGPT About AI Tools · Small Business · Automation 2026 Best AI Agents for Small Business in 2026: A Guide to Tools That Act as Virtual Employees By the aitrendblend.com Editorial Team · May 2026 · ~24 min

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Agentic AI for Personalized Knee Braces: How sEMG, Facial Expressions, and LLMs Combine to Configure Rehab Devices

Leave a Comment / Machine Learning, Agent Systems, Computer Vision, Medical AI /

Agentic AI for Personalized Knee Braces: How sEMG, Facial Expressions, and LLMs Combine to Configure Rehab Devices | AI Trend Blend AITrendBlend Machine Learning Computer Vision About Healthcare AI · Advanced Engineering Informatics 74 (2026) 104695 · 22 min read Your Knee Brace Said It Hurts. The AI Didn’t Believe It — Until the Muscle

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ARuleCon: How NUS Researchers Built an AI Agent That Translates Security Rules Between Any SIEM Platform

ARuleCon: How NUS Researchers Built an AI Agent That Translates Security Rules Between Any SIEM Platform

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ARuleCon: How NUS Researchers Built an AI Agent That Translates Security Rules Between Any SIEM Platform | AI Security Research AISecurity Research Agentic AI SIEM & SOC About AIOps / SIEM Security · arXiv:2604.06762v1 [cs.CR] · NUS & Fudan University · WWW ’26 · 17 min read ARuleCon: How NUS Researchers Built an AI Agent

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MetaClaw: The LLM Agent That Meta-Learns and Evolves in the Wild.

MetaClaw: The LLM Agent That Meta-Learns and Evolves in the Wild

Leave a Comment / Machine Learning, Agent Systems, Natural Language Processing /

MetaClaw: The LLM Agent That Meta-Learns and Evolves in the Wild | AI Trend Blend AITrendBlend Machine Learning Computer Vision About LLM Agents · Continual Learning · UNC-Chapel Hill · CMU · UC Santa Cruz · UC Berkeley (2026) · 25 min read MetaClaw: The LLM Agent That Meta-Learns and Evolves in the Wild —

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Goal-Oriented Graphs: How NTU Researchers Finally Taught LLMs to Plan Like Humans in Minecraft.

Goal-Oriented Graphs: How NTU Researchers Finally Taught LLMs to Plan Like Humans in Minecraft

Leave a Comment / Machine Learning, Agent Systems, Natural Language Processing /

Goal-Oriented Graphs: How NTU Researchers Finally Taught LLMs to Plan Like Humans in Minecraft | AI Trend Blend AITrendBlend Home ML Research NLP & LLMs Contact LLM Agents & Reasoning Goal-Oriented Graphs: How NTU Researchers Finally Taught LLMs to Plan Like Humans GraphRAG shreds procedural knowledge into thousands of disconnected fragments. A new framework from

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A New Framework That Teaches Multi-Agent Systems to Spot Unreliable Sensors.

When Drones Learn to Distrust: A New Framework That Teaches Multi-Agent Systems to Spot Unreliable Sensors

Leave a Comment / Machine Learning, Agent Systems /

When Drones Learn to Distrust: A New Framework That Teaches Multi-Agent Systems to Spot Unreliable Sensors AITrendBlend Machine Learning About Multi-Agent Systems · Information Fusion 133 (2026) 104261 · 18 min read When Drones Learn to Distrust: The Sensor Fusion Framework That Teaches Multi-Agent Systems to Spot Bad Data in Real Time Researchers at the

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AgentDropoutV2: Test-Time Rectify-or-Reject Pruning for Multi-Agent Systems.

AgentDropoutV2: Test-Time Rectify-or-Reject Pruning for Multi-Agent Systems

1 Comment / Machine Learning, Agent Systems /

AgentDropoutV2: Test-Time Rectify-or-Reject Pruning for Multi-Agent Systems | AI Security Research AISecurity Research Machine Learning About Multi-Agent Systems · arXiv:2602.23258v1 [cs.AI] · 16 min read AgentDropoutV2: Teaching Multi-Agent Systems to Self-Correct Through Test-Time Rectify-or-Reject Pruning A novel test-time framework that intercepts and iteratively rectifies erroneous agent outputs using retrieval-augmented adversarial indicators, achieving 6.3% accuracy improvement

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K2-Agent: The Cognitive Architecture That Taught AI to Think Like Humans About Mobile Tasks.

K2-Agent: Co-Evolving Know-What and Know-How for Hierarchical Mobile Device Control

Leave a Comment / Machine Learning, Agent Systems /

K2-Agent: Co-Evolving Know-What and Know-How for Hierarchical Mobile Device Control | AI Security Research AISecurity Research Machine Learning About Agent Systems · ICLR 2026 · 18 min read K2-Agent: The Cognitive Architecture That Taught AI to Think Like Humans About Mobile Tasks A hierarchical framework separates “knowing what” from “knowing how” — enabling co-evolution of

K2-Agent: Co-Evolving Know-What and Know-How for Hierarchical Mobile Device Control Read More »

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