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Language Models are Few-Shot Learners
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Language Models are Few-Shot Learners

28 May 2020
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
Prafulla Dhariwal
Arvind Neelakantan
Pranav Shyam
Girish Sastry
Amanda Askell
Sandhini Agarwal
Ariel Herbert-Voss
Gretchen Krueger
T. Henighan
R. Child
Aditya A. Ramesh
Daniel M. Ziegler
Jeff Wu
Clemens Winter
Christopher Hesse
Mark Chen
Eric Sigler
Ma-teusz Litwin
Scott Gray
B. Chess
Jack Clark
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
    BDL
ArXiv (abs)PDFHTML

Papers citing "Language Models are Few-Shot Learners"

32 / 12,482 papers shown
Title
Pre-trained Models for Natural Language Processing: A Survey
Pre-trained Models for Natural Language Processing: A Survey
Xipeng Qiu
Tianxiang Sun
Yige Xu
Yunfan Shao
Ning Dai
Xuanjing Huang
LM&MAVLM
413
1,500
0
18 Mar 2020
ReZero is All You Need: Fast Convergence at Large Depth
ReZero is All You Need: Fast Convergence at Large Depth
Thomas C. Bachlechner
Bodhisattwa Prasad Majumder
H. H. Mao
G. Cottrell
Julian McAuley
AI4CE
89
283
0
10 Mar 2020
Teaching Temporal Logics to Neural Networks
Teaching Temporal Logics to Neural Networks
Christopher Hahn
Frederik Schmitt
Jens U. Kreber
M. Rabe
Bernd Finkbeiner
NAI
109
67
0
06 Mar 2020
Iterative Averaging in the Quest for Best Test Error
Iterative Averaging in the Quest for Best Test Error
Diego Granziol
Xingchen Wan
Samuel Albanie
Stephen J. Roberts
74
3
0
02 Mar 2020
Loss landscapes and optimization in over-parameterized non-linear
  systems and neural networks
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks
Chaoyue Liu
Libin Zhu
M. Belkin
ODL
133
266
0
29 Feb 2020
On Biased Compression for Distributed Learning
On Biased Compression for Distributed Learning
Aleksandr Beznosikov
Samuel Horváth
Peter Richtárik
M. Safaryan
81
189
0
27 Feb 2020
A Primer in BERTology: What we know about how BERT works
A Primer in BERTology: What we know about how BERT works
Anna Rogers
Olga Kovaleva
Anna Rumshisky
OffRL
146
1,511
0
27 Feb 2020
Compressing Large-Scale Transformer-Based Models: A Case Study on BERT
Compressing Large-Scale Transformer-Based Models: A Case Study on BERT
Prakhar Ganesh
Yao Chen
Xin Lou
Mohammad Ali Khan
Yifan Yang
Hassan Sajjad
Preslav Nakov
Deming Chen
Marianne Winslett
AI4CE
148
201
0
27 Feb 2020
Training Large Neural Networks with Constant Memory using a New
  Execution Algorithm
Training Large Neural Networks with Constant Memory using a New Execution Algorithm
B. Pudipeddi
Maral Mesmakhosroshahi
Jinwen Xi
S. Bharadwaj
105
58
0
13 Feb 2020
Towards Crowdsourced Training of Large Neural Networks using
  Decentralized Mixture-of-Experts
Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts
Max Ryabinin
Anton I. Gusev
FedML
91
52
0
10 Feb 2020
Language Models Are An Effective Patient Representation Learning
  Technique For Electronic Health Record Data
Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data
E. Steinberg
Kenneth Jung
Jason Alan Fries
Conor K. Corbin
Stephen Pfohl
N. Shah
94
112
0
06 Jan 2020
Fast and energy-efficient neuromorphic deep learning with first-spike
  times
Fast and energy-efficient neuromorphic deep learning with first-spike times
Julian Goltz
Laura Kriener
A. Baumbach
Sebastian Billaudelle
O. Breitwieser
...
Á. F. Kungl
Walter Senn
Johannes Schemmel
K. Meier
Mihai A. Petrovici
163
132
0
24 Dec 2019
Extending Machine Language Models toward Human-Level Language
  Understanding
Extending Machine Language Models toward Human-Level Language Understanding
James L. McClelland
Felix Hill
Maja R. Rudolph
Jason Baldridge
Hinrich Schütze
LRM
78
35
0
12 Dec 2019
Attentive Representation Learning with Adversarial Training for Short
  Text Clustering
Attentive Representation Learning with Adversarial Training for Short Text Clustering
Wei Zhang
Chao Dong
Jianhua Yin
Jianyong Wang
74
13
0
08 Dec 2019
Blockwise Self-Attention for Long Document Understanding
Blockwise Self-Attention for Long Document Understanding
J. Qiu
Hao Ma
Omer Levy
Scott Yih
Sinong Wang
Jie Tang
111
254
0
07 Nov 2019
Discovering the Compositional Structure of Vector Representations with
  Role Learning Networks
Discovering the Compositional Structure of Vector Representations with Role Learning Networks
Paul Soulos
R. Thomas McCoy
Tal Linzen
P. Smolensky
CoGe
132
44
0
21 Oct 2019
Demon: Improved Neural Network Training with Momentum Decay
Demon: Improved Neural Network Training with Momentum Decay
John Chen
Cameron R. Wolfe
Zhaoqi Li
Anastasios Kyrillidis
ODL
106
15
0
11 Oct 2019
On the adequacy of untuned warmup for adaptive optimization
On the adequacy of untuned warmup for adaptive optimization
Jerry Ma
Denis Yarats
106
70
0
09 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential
  equations based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Lu Lu
Pengzhan Jin
George Karniadakis
254
2,180
0
08 Oct 2019
Soft-Label Dataset Distillation and Text Dataset Distillation
Soft-Label Dataset Distillation and Text Dataset Distillation
Ilia Sucholutsky
Matthias Schonlau
DD
170
135
0
06 Oct 2019
Distributed Learning of Deep Neural Networks using Independent Subnet
  Training
Distributed Learning of Deep Neural Networks using Independent Subnet Training
John Shelton Hyatt
Cameron R. Wolfe
Michael Lee
Yuxin Tang
Anastasios Kyrillidis
Christopher M. Jermaine
OOD
92
39
0
04 Oct 2019
Semi-supervised Thai Sentence Segmentation Using Local and Distant Word
  Representations
Semi-supervised Thai Sentence Segmentation Using Local and Distant Word Representations
Chanatip Saetia
Ekapol Chuangsuwanich
Tawunrat Chalothorn
P. Vateekul
74
5
0
04 Aug 2019
Trends in Integration of Vision and Language Research: A Survey of
  Tasks, Datasets, and Methods
Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
Aditya Mogadala
M. Kalimuthu
Dietrich Klakow
VLM
141
136
0
22 Jul 2019
Norms for Beneficial A.I.: A Computational Analysis of the Societal
  Value Alignment Problem
Norms for Beneficial A.I.: A Computational Analysis of the Societal Value Alignment Problem
Pedro M. Fernandes
Francisco C. Santos
Manuel Lopes
45
11
0
26 Jun 2019
Exposure Bias versus Self-Recovery: Are Distortions Really Incremental
  for Autoregressive Text Generation?
Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation?
Tianxing He
Jingzhao Zhang
Zhiming Zhou
James R. Glass
111
32
0
25 May 2019
An Information Theoretic Interpretation to Deep Neural Networks
An Information Theoretic Interpretation to Deep Neural Networks
Shao-Lun Huang
Xiangxiang Xu
Lizhong Zheng
G. Wornell
FAtt
95
44
0
16 May 2019
An Attentive Survey of Attention Models
An Attentive Survey of Attention Models
S. Chaudhari
Varun Mithal
Gungor Polatkan
R. Ramanath
194
666
0
05 Apr 2019
A Brain-inspired Algorithm for Training Highly Sparse Neural Networks
A Brain-inspired Algorithm for Training Highly Sparse Neural Networks
Zahra Atashgahi
Joost Pieterse
Shiwei Liu
Decebal Constantin Mocanu
Raymond N. J. Veldhuis
Mykola Pechenizkiy
83
15
0
17 Mar 2019
Investigating Antigram Behaviour using Distributional Semantics
Investigating Antigram Behaviour using Distributional Semantics
Saptarshi Sengupta
36
0
0
15 Jan 2019
Automated Machine Learning: From Principles to Practices
Automated Machine Learning: From Principles to Practices
Quanming Yao
Mengshuo Wang
Hugo Jair Escalante
Huan Zhao
Qiang Yang
121
259
0
31 Oct 2018
Deep Learning for Genomics: A Concise Overview
Deep Learning for Genomics: A Concise Overview
Tianwei Yue
Yuanxin Wang
Longxiang Zhang
Chunming Gu
Haohan Wang
Wenping Wang
Qi Lyu
Yujie Dun
AILawVLMBDL
86
91
0
02 Feb 2018
Quantifying the probable approximation error of probabilistic inference
  programs
Quantifying the probable approximation error of probabilistic inference programs
Marco F. Cusumano-Towner
Vikash K. Mansinghka
100
7
0
31 May 2016
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