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Input Compression with Positional Consistency for Efficient Training and
  Inference of Transformer Neural Networks

Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks

22 November 2023
Amrit Nagarajan
Anand Raghunathan
    VLM
    ViT
ArXivPDFHTML

Papers citing "Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks"

2 / 2 papers shown
Title
Scaling Laws for Neural Language Models
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
264
4,505
0
23 Jan 2020
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
299
6,984
0
20 Apr 2018
1