GTA-2 benchmark shows frontier models achieve below 50% on atomic tool tasks and only 14.39% success on realistic long-horizon workflows, with execution harnesses like Manus providing substantial gains.
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QuadAgent uses an asynchronous multi-agent architecture with an Impression Graph for scene memory and vision-based avoidance to enable training-free vision-language guided agile quadrotor flight, outperforming baselines in simulations and achieving real-world speeds up to 5 m/s.
AgenticQwen small models trained via reasoning and agentic RL with dual data flywheels achieve strong benchmark performance and close the gap to larger models on industrial search and data analysis tasks.
GenericAgent outperforms other LLM agents on long-horizon tasks by maximizing context information density with fewer tokens via minimal tools, on-demand memory, trajectory-to-SOP evolution, and compression.
BiasIG is a multi-dimensional benchmark for social biases in T2I models that shows debiasing interventions frequently cause confounding discrimination effects.
Self-sovereign agents are AI systems that economically sustain and extend their operation without human involvement; the paper analyzes remaining technical barriers and discusses associated security, societal, and governance challenges.
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Self-Sovereign Agent
Self-sovereign agents are AI systems that economically sustain and extend their operation without human involvement; the paper analyzes remaining technical barriers and discusses associated security, societal, and governance challenges.