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cs.LG2024
Meta-Learning for Speeding Up Large Model Inference in Decentralized Environments
Yuzhe Yang, Yipeng Du, Ahmad Farhan +6
The deployment of large-scale models, such as large language models (LLMs) and sophisticated image generation systems, incurs substantial costs due to their computational demands.…
cs.AI2024
Model Agnostic Hybrid Sharding For Heterogeneous Distributed Inference
Claudio Angione, Yue Zhao, Harry Yang +4
The rapid growth of large-scale AI models, particularly large language models has brought significant challenges in data privacy, computational resources, and accessibility. Tradit…
cs.CR2024★ 1 cited
Towards Secure and Private AI: A Framework for Decentralized Inference
Hongyang Zhang, Yue Zhao, Claudio Angione +5
The rapid advancement of ML models in critical sectors such as healthcare, finance, and security has intensified the need for robust data security, model integrity, and reliable ou…