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Prompt Refinement or Fine-tuning? Best Practices for using LLMs in
  Computational Social Science Tasks

Prompt Refinement or Fine-tuning? Best Practices for using LLMs in Computational Social Science Tasks

2 August 2024
Anders Giovanni Moller
L. Aiello
    LLMAG
ArXivPDFHTML

Papers citing "Prompt Refinement or Fine-tuning? Best Practices for using LLMs in Computational Social Science Tasks"

3 / 3 papers shown
Title
A Picture is Worth a Thousand Prompts? Efficacy of Iterative Human-Driven Prompt Refinement in Image Regeneration Tasks
A Picture is Worth a Thousand Prompts? Efficacy of Iterative Human-Driven Prompt Refinement in Image Regeneration Tasks
Khoi Trinh
S. Seidenberger
Raveen Wijewickrama
Murtuza Jadliwala
Anindya Maiti
108
0
0
29 Apr 2025
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
298
4,077
0
24 May 2022
Training language models to follow instructions with human feedback
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
306
11,909
0
04 Mar 2022
1