Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding

26 February 2024

Papers citing "Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding"

6 / 6 papers shown

Title
Exploring Gen-AI applications in building research and industry: A review Hanlong Wan Jian Zhang Yan Chen Weili Xu Fan Feng AI4CE 37 0 0 01 Oct 2024
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Lokesh Nagalapatti Chun-Liang Li Chih-Kuan Yeh Hootan Nakhost Yasuhisa Fujii Alexander Ratner Ranjay Krishna Chen-Yu Lee Tomas Pfister ALM 204 498 0 03 May 2023
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 278 3,784 0 18 Apr 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 223 4,424 0 23 Jan 2020
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,724 0 26 Sep 2016
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 170 3,504 0 10 Jun 2015