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PaLM: Scaling Language Modeling with Pathways
v1v2v3v4v5 (latest)

PaLM: Scaling Language Modeling with Pathways

5 April 2022
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Gaurav Mishra
Adam Roberts
P. Barham
Hyung Won Chung
Charles Sutton
Sebastian Gehrmann
Parker Schuh
Kensen Shi
Sasha Tsvyashchenko
Joshua Maynez
Abhishek Rao
Parker Barnes
Yi Tay
Noam M. Shazeer
Vinodkumar Prabhakaran
Emily Reif
Nan Du
Ben Hutchinson
Reiner Pope
James Bradbury
Jacob Austin
Michael Isard
Guy Gur-Ari
Pengcheng Yin
Toju Duke
Anselm Levskaya
Sanjay Ghemawat
Sunipa Dev
Henryk Michalewski
Xavier Garcia
Vedant Misra
Kevin Robinson
Liam Fedus
Denny Zhou
Daphne Ippolito
D. Luan
Hyeontaek Lim
Barret Zoph
A. Spiridonov
Ryan Sepassi
David Dohan
Shivani Agrawal
Mark Omernick
Andrew M. Dai
Thanumalayan Sankaranarayana Pillai
Marie Pellat
Aitor Lewkowycz
Erica Moreira
R. Child
Oleksandr Polozov
Katherine Lee
Zongwei Zhou
Xuezhi Wang
Brennan Saeta
Mark Díaz
Orhan Firat
Michele Catasta
Jason W. Wei
Kathy Meier-Hellstern
Douglas Eck
J. Dean
Slav Petrov
Noah Fiedel
    PILMLRM
ArXiv (abs)PDFHTML

Papers citing "PaLM: Scaling Language Modeling with Pathways"

50 / 4,332 papers shown
Title
Automatic Prompt Augmentation and Selection with Chain-of-Thought from
  Labeled Data
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data
Kashun Shum
Shizhe Diao
Tong Zhang
ReLMLRM
121
138
0
24 Feb 2023
Check Your Facts and Try Again: Improving Large Language Models with
  External Knowledge and Automated Feedback
Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback
Baolin Peng
Michel Galley
Pengcheng He
Hao Cheng
Yujia Xie
...
Qiuyuan Huang
Lars Liden
Zhou Yu
Weizhu Chen
Jianfeng Gao
KELMHILMLRM
118
402
0
24 Feb 2023
Language-Driven Representation Learning for Robotics
Language-Driven Representation Learning for Robotics
Siddharth Karamcheti
Suraj Nair
Annie S. Chen
Thomas Kollar
Chelsea Finn
Dorsa Sadigh
Percy Liang
LM&RoSSL
138
156
0
24 Feb 2023
MUX-PLMs: Data Multiplexing for High-throughput Language Models
MUX-PLMs: Data Multiplexing for High-throughput Language Models
Vishvak Murahari
Ameet Deshpande
Carlos E. Jimenez
Izhak Shafran
Mingqiu Wang
Yuan Cao
Karthik Narasimhan
MoE
63
5
0
24 Feb 2023
In What Languages are Generative Language Models the Most Formal?
  Analyzing Formality Distribution across Languages
In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across Languages
Asim Ersoy
Gerson Vizcarra
T. Mayeesha
Benjamin Muller
72
2
0
23 Feb 2023
Active Prompting with Chain-of-Thought for Large Language Models
Active Prompting with Chain-of-Thought for Large Language Models
Shizhe Diao
Pengcheng Wang
Yong Lin
Tong Zhang
ReLMKELMLLMAGLRM
137
133
0
23 Feb 2023
On the Generalization Ability of Retrieval-Enhanced Transformers
On the Generalization Ability of Retrieval-Enhanced Transformers
Tobias Norlund
Ehsan Doostmohammadi
Richard Johansson
Marco Kuhlmann
RALM
67
6
0
23 Feb 2023
Sentence Simplification via Large Language Models
Sentence Simplification via Large Language Models
Yutao Feng
Jipeng Qiang
Yun Li
Yunhao Yuan
Yi Zhu
94
19
0
23 Feb 2023
Can Pre-trained Vision and Language Models Answer Visual
  Information-Seeking Questions?
Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?
Yang Chen
Hexiang Hu
Yi Luan
Haitian Sun
Soravit Changpinyo
Alan Ritter
Ming-Wei Chang
152
94
0
23 Feb 2023
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep
  Learning Serving
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving
Zhuohan Li
Lianmin Zheng
Yinmin Zhong
Vincent Liu
Ying Sheng
...
Yanping Huang
Zhifeng Chen
Hao Zhang
Joseph E. Gonzalez
Ion Stoica
MoE
59
68
0
22 Feb 2023
Scaling Robot Learning with Semantically Imagined Experience
Scaling Robot Learning with Semantically Imagined Experience
Tianhe Yu
Ted Xiao
Austin Stone
Jonathan Tompson
Anthony Brohan
...
M. Dee
Jodilyn Peralta
Brian Ichter
Karol Hausman
F. Xia
LM&RoDiffM
98
155
0
22 Feb 2023
How Does In-Context Learning Help Prompt Tuning?
How Does In-Context Learning Help Prompt Tuning?
Simeng Sun
Yang Liu
Dan Iter
Chenguang Zhu
Mohit Iyyer
VLM
72
19
0
22 Feb 2023
Guiding Large Language Models via Directional Stimulus Prompting
Guiding Large Language Models via Directional Stimulus Prompting
Zekun Li
Baolin Peng
Pengcheng He
Michel Galley
Jianfeng Gao
Xi Yan
LLMAGLRMLM&Ro
139
101
0
22 Feb 2023
Open-domain Visual Entity Recognition: Towards Recognizing Millions of
  Wikipedia Entities
Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities
Hexiang Hu
Yi Luan
Yang Chen
Urvashi Khandelwal
Mandar Joshi
Kenton Lee
Kristina Toutanova
Ming-Wei Chang
VLM
136
61
0
22 Feb 2023
Optical Transformers
Optical Transformers
Maxwell G. Anderson
Shifan Ma
Tianyu Wang
Logan G. Wright
Peter L. McMahon
51
23
0
20 Feb 2023
Learning Deep Semantics for Test Completion
Learning Deep Semantics for Test Completion
Pengyu Nie
Rahul Banerjee
Junyi Jessy Li
Raymond J. Mooney
Miloš Gligorić
109
63
0
20 Feb 2023
Poisoning Web-Scale Training Datasets is Practical
Poisoning Web-Scale Training Datasets is Practical
Nicholas Carlini
Matthew Jagielski
Christopher A. Choquette-Choo
Daniel Paleka
Will Pearce
Hyrum S. Anderson
Andreas Terzis
Kurt Thomas
Florian Tramèr
SILM
131
204
0
20 Feb 2023
TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training
TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training
Chang-Qin Chen
Min Li
Zhihua Wu
Dianhai Yu
Chao Yang
MoE
61
15
0
20 Feb 2023
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation
  in Natural Language Generation
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
Lorenz Kuhn
Y. Gal
Sebastian Farquhar
UQLM
244
313
0
19 Feb 2023
Can ChatGPT Understand Too? A Comparative Study on ChatGPT and
  Fine-tuned BERT
Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT
Qihuang Zhong
Liang Ding
Juhua Liu
Bo Du
Dacheng Tao
AI4MH
148
245
0
19 Feb 2023
Learning Language Representations with Logical Inductive Bias
Learning Language Representations with Logical Inductive Bias
Jianshu Chen
NAIAI4CELRM
55
3
0
19 Feb 2023
Machine Love
Machine Love
Joel Lehman
129
5
0
18 Feb 2023
How Good Are GPT Models at Machine Translation? A Comprehensive
  Evaluation
How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation
Amr Hendy
M. Abdelrehim
Amr Sharaf
Vikas Raunak
Mohamed Gabr
Hitokazu Matsushita
Young Jin Kim
Mohamed Afify
Hany Awadalla
ELMLM&MAAI4CE
85
441
0
18 Feb 2023
RETVec: Resilient and Efficient Text Vectorizer
RETVec: Resilient and Efficient Text Vectorizer
Elie Bursztein
Marina Zhang
Owen Vallis
Xinyu Jia
Alexey Kurakin
VLM
82
4
0
18 Feb 2023
Bounding the Capabilities of Large Language Models in Open Text
  Generation with Prompt Constraints
Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints
Albert Lu
Hongxin Zhang
Yanzhe Zhang
Xuezhi Wang
Diyi Yang
LRM
85
32
0
17 Feb 2023
Improving Training Stability for Multitask Ranking Models in Recommender
  Systems
Improving Training Stability for Multitask Ranking Models in Recommender Systems
Jiaxi Tang
Yoel Drori
Daryl Chang
M. Sathiamoorthy
Justin Gilmer
Li Wei
Xinyang Yi
Lichan Hong
Ed H. Chi
100
10
0
17 Feb 2023
Complex QA and language models hybrid architectures, Survey
Complex QA and language models hybrid architectures, Survey
Xavier Daull
P. Bellot
Emmanuel Bruno
Vincent Martin
Elisabeth Murisasco
ELM
221
16
0
17 Feb 2023
Multiperiodic Processes: Ergodic Sources with a Sublinear Entropy
Multiperiodic Processes: Ergodic Sources with a Sublinear Entropy
L. Debowski
MILM
122
11
0
17 Feb 2023
Auditing large language models: a three-layered approach
Auditing large language models: a three-layered approach
Jakob Mokander
Jonas Schuett
Hannah Rose Kirk
Luciano Floridi
AILawMLAU
169
216
0
16 Feb 2023
LEVER: Learning to Verify Language-to-Code Generation with Execution
LEVER: Learning to Verify Language-to-Code Generation with Execution
Ansong Ni
Srini Iyer
Dragomir R. Radev
Ves Stoyanov
Wen-tau Yih
Sida I. Wang
Xi Lin
145
227
0
16 Feb 2023
Auto-Parallelizing Large Models with Rhino: A Systematic Approach on
  Production AI Platform
Auto-Parallelizing Large Models with Rhino: A Systematic Approach on Production AI Platform
Shiwei Zhang
Lansong Diao
Siyu Wang
Zongyan Cao
Yiliang Gu
Chang Si
Ziji Shi
Zhen Zheng
Chuan Wu
W. Lin
AI4CE
61
4
0
16 Feb 2023
Slapo: A Schedule Language for Progressive Optimization of Large Deep
  Learning Model Training
Slapo: A Schedule Language for Progressive Optimization of Large Deep Learning Model Training
Hongzheng Chen
Cody Hao Yu
Shuai Zheng
Zhen Zhang
Zhiru Zhang
Yida Wang
84
8
0
16 Feb 2023
ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence
ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence
D. Rivkin
Gregory Dudek
Nikhil Kakodkar
David Meger
Oliver Limoyo
Xue Liu
F. Hogan
LM&Ro
69
6
0
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Platform-Independent and Curriculum-Oriented Intelligent Assistant for
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Platform-Independent and Curriculum-Oriented Intelligent Assistant for Higher Education
Ramteja Sajja
Y. Sermet
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Ibrahim Demir
60
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0
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Speculative Decoding with Big Little Decoder
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K. Mangalam
Suhong Moon
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MoE
147
113
0
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Augmented Language Models: a Survey
Grégoire Mialon
Roberto Dessì
Maria Lomeli
Christoforos Nalmpantis
Ramakanth Pasunuru
...
Jane Dwivedi-Yu
Asli Celikyilmaz
Edouard Grave
Yann LeCun
Thomas Scialom
LRMKELM
105
394
0
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Studying the effect of AI Code Generators on Supporting Novice Learners
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Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
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J. Chow
Carl Ka To Ma
B. Ericson
David Weintrop
Tovi Grossman
AI4EdELM
56
228
0
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Adding Instructions during Pretraining: Effective Way of Controlling
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Adding Instructions during Pretraining: Effective Way of Controlling Toxicity in Language Models
Shrimai Prabhumoye
M. Patwary
Mohammad Shoeybi
Bryan Catanzaro
LM&MA
59
21
0
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Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey
Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey
L. Delong
Ramon Fernández Mir
Jacques D. Fleuriot
NAI
126
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On the Planning Abilities of Large Language Models (A Critical
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On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)
Karthik Valmeekam
S. Sreedharan
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Alberto Olmo Hernandez
Subbarao Kambhampati
LLMAGLRM
82
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Gradient-Based Automated Iterative Recovery for Parameter-Efficient
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Towards Agile Text Classifiers for Everyone
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A Unified View of Long-Sequence Models towards Modeling Million-Scale
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Marko Kabić
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Expediting Distributed DNN Training with Device Topology-Aware Graph
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Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment
Shiwei Zhang
Xiaodong Yi
Lansong Diao
Chuan Wu
Siyu Wang
W. Lin
GNN
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The Framework Tax: Disparities Between Inference Efficiency in NLP
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The Framework Tax: Disparities Between Inference Efficiency in NLP Research and Deployment
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Jacob Kahn
Clara Na
Yonatan Bisk
Emma Strubell
FedML
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Policy-Induced Self-Supervision Improves Representation Finetuning in
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Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL
Sébastien M. R. Arnold
Fei Sha
SSL
57
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Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation
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Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification
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Hongfa Wu
Wei-Yao Wang
Chao-Han Huck Yang
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Transformer models: an introduction and catalog
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X. Amatriain
Ananth Sankar
Jie Bing
Praveen Kumar Bodigutla
Timothy J. Hazen
Michaeel Kazi
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Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented
  Large Language Models
Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models
Renat Aksitov
Chung-Ching Chang
David Reitter
Siamak Shakeri
Yun-hsuan Sung
RALM
80
16
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Distillation of encoder-decoder transformers for sequence labelling
Distillation of encoder-decoder transformers for sequence labelling
M. Farina
D. Pappadopulo
Anant Gupta
Leslie Huang
Ozan Irsoy
Thamar Solorio
VLM
205
3
0
10 Feb 2023
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