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2310.10707
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Demonstrations Are All You Need: Advancing Offensive Content Paraphrasing using In-Context Learning
16 October 2023
Anirudh Som
Karan Sikka
Helen Gent
Ajay Divakaran
A. Kathol
D. Vergyri
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Papers citing
"Demonstrations Are All You Need: Advancing Offensive Content Paraphrasing using In-Context Learning"
7 / 7 papers shown
Title
Can large language models explore in-context?
Akshay Krishnamurthy
Keegan Harris
Dylan J. Foster
Cyril Zhang
Aleksandrs Slivkins
LM&Ro
LLMAG
LRM
123
23
0
22 Mar 2024
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu
Haotian Ye
Lei Xing
James Y. Zou
26
84
0
11 Nov 2023
Mixture of Soft Prompts for Controllable Data Generation
Derek Chen
Celine Lee
Yunan Lu
Domenic Rosati
Zhou Yu
114
22
0
02 Mar 2023
APPDIA: A Discourse-aware Transformer-based Style Transfer Model for Offensive Social Media Conversations
Katherine Atwell
Sabit Hassan
Malihe Alikhani
54
30
0
17 Sep 2022
Meta-learning via Language Model In-context Tuning
Yanda Chen
Ruiqi Zhong
Sheng Zha
George Karypis
He He
234
156
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
What Makes Good In-Context Examples for GPT-
3
3
3
?
Jiachang Liu
Dinghan Shen
Yizhe Zhang
Bill Dolan
Lawrence Carin
Weizhu Chen
AAML
RALM
275
1,312
0
17 Jan 2021
1