6 citations · 23 across the 15 of their papers we have counts for
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cs.AI2024
Fine-Tuning and Deploying Large Language Models Over Edges: Issues and Approaches
Yanjie Dong, Haijun Zhang, Chengming Li +3
Since the release of GPT2-1.5B in 2019, the large language models (LLMs) have evolved from specialized deep models to versatile foundation models. While demonstrating remarkable ze…
cs.AI2024★ 1 cited
CLHA: A Simple yet Effective Contrastive Learning Framework for Human Alignment
Feiteng Fang, Liang Zhu, Min Yang +6
Reinforcement learning from human feedback (RLHF) is a crucial technique in aligning large language models (LLMs) with human preferences, ensuring these LLMs behave in beneficial a…