1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 1 cited
LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference
Qichen Fu, Minsik Cho, Thomas Merth +3
The inference of transformer-based large language models consists of two sequential stages: 1) a prefilling stage to compute the KV cache of prompts and generate the first token, a…
cs.CL2024
Speculative Streaming: Fast LLM Inference without Auxiliary Models
Nikhil Bhendawade, Irina Belousova, Qichen Fu +3
Speculative decoding is a prominent technique to speed up the inference of a large target language model based on predictions of an auxiliary draft model. While effective, in appli…
cs.LG2023
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models
Minsik Cho, Keivan A. Vahid, Qichen Fu +5
Since Large Language Models or LLMs have demonstrated high-quality performance on many complex language tasks, there is a great interest in bringing these LLMs to mobile devices fo…