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Cheap Learning: Maximising Performance of Language Models for Social
  Data Science Using Minimal Data

Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data

22 January 2024
Leonardo Castro-Gonzalez
Yi-Ling Chung
Hannak Rose Kirk
John Francis
Angus R. Williams
Pica Johansson
Jonathan Bright
ArXivPDFHTML

Papers citing "Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data"

9 / 9 papers shown
Title
Distilling Step-by-Step! Outperforming Larger Language Models with Less
  Training Data and Smaller Model Sizes
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
Drawing Causal Inferences About Performance Effects in NLP
Drawing Causal Inferences About Performance Effects in NLP
Sandra Wankmüller
CML
11
1
0
14 Sep 2022
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLM
LRM
291
2,712
0
24 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason W. Wei
Xuezhi Wang
Dale Schuurmans
Maarten Bosma
Brian Ichter
F. Xia
Ed H. Chi
Quoc Le
Denny Zhou
LM&Ro
LRM
AI4CE
ReLM
315
8,261
0
28 Jan 2022
Towards Efficient Post-training Quantization of Pre-trained Language
  Models
Towards Efficient Post-training Quantization of Pre-trained Language Models
Haoli Bai
Lu Hou
Lifeng Shang
Xin Jiang
Irwin King
M. Lyu
MQ
53
47
0
30 Sep 2021
Exploiting Cloze Questions for Few Shot Text Classification and Natural
  Language Inference
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick
Hinrich Schütze
253
1,584
0
21 Jan 2020
Language Models as Knowledge Bases?
Language Models as Knowledge Bases?
Fabio Petroni
Tim Rocktaschel
Patrick Lewis
A. Bakhtin
Yuxiang Wu
Alexander H. Miller
Sebastian Riedel
KELM
AI4MH
396
2,576
0
03 Sep 2019
Are We Modeling the Task or the Annotator? An Investigation of Annotator
  Bias in Natural Language Understanding Datasets
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets
Mor Geva
Yoav Goldberg
Jonathan Berant
235
319
0
21 Aug 2019
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
273
2,878
0
15 Sep 2016
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