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When Linear Attention Meets Autoregressive Decoding: Towards More
  Effective and Efficient Linearized Large Language Models

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

11 June 2024
Haoran You
Yichao Fu
Zheng Wang
Amir Yazdanbakhsh
Yingyan Celine Lin
ArXivPDFHTML

Papers citing "When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models"

4 / 4 papers shown
Title
MiniGPT-v2: large language model as a unified interface for
  vision-language multi-task learning
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
Jun Chen
Deyao Zhu
Xiaoqian Shen
Xiang Li
Zechun Liu
Pengchuan Zhang
Raghuraman Krishnamoorthi
Vikas Chandra
Yunyang Xiong
Mohamed Elhoseiny
MLLM
160
280
0
14 Oct 2023
Transformer Quality in Linear Time
Transformer Quality in Linear Time
Weizhe Hua
Zihang Dai
Hanxiao Liu
Quoc V. Le
71
220
0
21 Feb 2022
Zero-Shot Text-to-Image Generation
Zero-Shot Text-to-Image Generation
Aditya A. Ramesh
Mikhail Pavlov
Gabriel Goh
Scott Gray
Chelsea Voss
Alec Radford
Mark Chen
Ilya Sutskever
VLM
253
4,735
0
24 Feb 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
294
6,927
0
20 Apr 2018
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