AI RESEARCH
Multi-Turn Reasoning LLMs for Task Offloading in Mobile Edge Computing
arXiv CS.LG
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ArXi:2604.07148v1 Announce Type: new Emerging computation-intensive applications impose stringent latency requirements on resource-constrained mobile devices. Mobile Edge Computing (MEC) addresses this challenge through task offloading. However, designing effective policies remains difficult due to dynamic task arrivals, time-varying channels, and the spatio-temporal coupling of server queues. Conventional heuristics lack adaptability, while Deep Reinforcement Learning (DRL) suffers from limited generalization and architectural rigidity, requiring re