EAT, an attention-guided diffusion reinforcement learning scheduler for collaborative edge AIGC, reduces Stable Diffusion inference latency by 56-74% versus baselines while keeping CLIP quality nearly unchanged.
Ai- generated incentive mechanism and full-duplex semantic communica- tions for information sharing,
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EAT: QoS-Aware Edge-Collaborative AIGC Task Scheduling via Attention-Guided Diffusion Reinforcement Learning
EAT, an attention-guided diffusion reinforcement learning scheduler for collaborative edge AIGC, reduces Stable Diffusion inference latency by 56-74% versus baselines while keeping CLIP quality nearly unchanged.