101 citations · 166 across the 11 of their papers we have counts for
3 papers · 1 filter
Accelerating Retrieval-Augmented Language Model Serving with Speculation
Zhihao Zhang, Alan Zhu, Lijie Yang +4
Retrieval-augmented language models (RaLM) have demonstrated the potential to solve knowledge-intensive natural language processing (NLP) tasks by combining a non-parametric knowle…
Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models
Zhengxin Zhang, Dan Zhao, Xupeng Miao +4
Finetuning large language models (LLMs) has been empirically effective on a variety of downstream tasks. Existing approaches to finetuning an LLM either focus on parameter-efficien…
Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang +4
In the rapidly evolving landscape of artificial intelligence (AI), generative large language models (LLMs) stand at the forefront, revolutionizing how we interact with our data. Ho…