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cs.LG2025
OTARo: Once Tuning for All Precisions toward Robust On-Device LLMs
Shaoyuan Chen, Zhixuan Chen, Dawei Yang +2
Large Language Models (LLMs) fine-tuning techniques not only improve the adaptability to diverse downstream tasks, but also mitigate adverse effects of model quantization. Despite…
cs.LG2025
Efficient Heterogeneous Large Language Model Decoding with Model-Attention Disaggregation
Shaoyuan Chen, Wencong Xiao, Yutong Lin +5
Transformer-based large language models (LLMs) exhibit impressive performance in generative tasks but also introduce significant challenges in real-world serving due to inefficient…
cs.LG2024
Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients
Shaoyuan Chen, Linlin You, Rui Liu +2
The training of large models, involving fine-tuning, faces the scarcity of high-quality data. Compared to the solutions based on centralized data centers, updating large models in…