A multi-agent architecture using compact VLMs on edge hardware controls a mobile manipulator across five warehouse task categories in hardware-in-the-loop simulation.
arXiv preprint arXiv:2603.03148 , year=
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Survey framing LLM agents as model-plus-harness systems, decomposing harness responsibilities, mapping them to tasks, and highlighting open challenges in evaluation, safety, and co-evolution.
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Multi-Agent Robotic Control with Onboard Vision-Language Models
A multi-agent architecture using compact VLMs on edge hardware controls a mobile manipulator across five warehouse task categories in hardware-in-the-loop simulation.
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From Question Answering to Task Completion: A Survey on Agent System and Harness Design
Survey framing LLM agents as model-plus-harness systems, decomposing harness responsibilities, mapping them to tasks, and highlighting open challenges in evaluation, safety, and co-evolution.