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2308.03958
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Simple synthetic data reduces sycophancy in large language models
7 August 2023
Jerry W. Wei
Da Huang
Yifeng Lu
Denny Zhou
Quoc V. Le
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Papers citing
"Simple synthetic data reduces sycophancy in large language models"
6 / 56 papers shown
Title
Improving alignment of dialogue agents via targeted human judgements
Amelia Glaese
Nat McAleese
Maja Trkebacz
John Aslanides
Vlad Firoiu
...
John F. J. Mellor
Demis Hassabis
Koray Kavukcuoglu
Lisa Anne Hendricks
G. Irving
ALM
AAML
230
506
0
28 Sep 2022
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
339
12,003
0
04 Mar 2022
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
398
8,559
0
28 Jan 2022
Multitask Prompted Training Enables Zero-Shot Task Generalization
Victor Sanh
Albert Webson
Colin Raffel
Stephen H. Bach
Lintang Sutawika
...
T. Bers
Stella Biderman
Leo Gao
Thomas Wolf
Alexander M. Rush
LRM
213
1,661
0
15 Oct 2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Yao Lu
Max Bartolo
Alastair Moore
Sebastian Riedel
Pontus Stenetorp
AILaw
LRM
279
1,124
0
18 Apr 2021
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
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