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cs.CL2024
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
Rana Muhammad Shahroz Khan, Pingzhi Li, Sukwon Yun +4
As large language models (LLMs) increasingly shape the AI landscape, fine-tuning pretrained models has become more popular than in the pre-LLM era for achieving optimal performance…
cs.CV2024
Characterizing Disparity Between Edge Models and High-Accuracy Base Models for Vision Tasks
Zhenyu Wang, Shahriar Nirjon
Edge devices, with their widely varying capabilities, support a diverse range of edge AI models. This raises the question: how does an edge model differ from a high-accuracy (base)…