AIBullisharXiv – CS AI · Mar 167/10
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ARL-Tangram: Unleash the Resource Efficiency in Agentic Reinforcement Learning
Researchers introduced ARL-Tangram, a resource management system that optimizes cloud resource allocation for agentic reinforcement learning tasks involving large language models. The system achieves up to 4.3x faster action completion times and 71.2% resource savings through action-level orchestration, and has been deployed for training MiMo series models.