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20242026
most citedEDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

1 citations · 1 across the 8 of their papers we have counts for

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cs.CV2024

GiVE: Guiding Visual Encoder to Perceive Overlooked Information

Junjie Li, Jianghong Ma, Xiaofeng Zhang +2

Multimodal Large Language Models have advanced AI in applications like text-to-video generation and visual question answering. These models rely on visual encoders to convert non-t…

cs.LG2024★ 1 cited

EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

Zhongzhi Yu, Zheng Wang, Yuhan Li +6

Efficient adaption of large language models (LLMs) on edge devices is essential for applications requiring continuous and privacy-preserving adaptation and inference. However, exis…