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A tutorial on fine-tuning pretrained language models: Applications in social and behavioral science research
15 references·0 citing·45 second hop
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References

  • 2002Psychological Aspects of Natural Language Use: Our Words, Our Selves2,616 cited
  • 2023ChatGPT outperforms crowd workers for text-annotation tasks1,193 cited
  • 2023Out of One, Many: Using Language Models to Simulate Human Samples774 cited
  • 2023Can Large Language Models Transform Computational Social Science?582 cited
  • 2020Natural Language Analysis and the Psychology of Verbal Behavior: The Past, Present, and Future States of the Field316 cited
  • 2024Loneliness and suicide mitigation for students using GPT3-enabled chatbots248 cited
  • 2023Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and BERT-NLI169 cited
  • 2025Using natural language processing to analyse text data in behavioural science140 cited
  • 2024The role of hyperparameters in machine learning models and how to tune them111 cited
  • 2023The text-package: An R-package for analyzing and visualizing human language using natural language processing and transformers.61 cited
  • 2024Quantitative text analysis30 cited
  • 2022Using natural language processing and machine learning to replace human content coders.29 cited
  • 2024Promotional language and the adoption of innovative ideas in science26 cited
  • 2023Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction

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21 cited
  • 2023On Finetuning Large Language Models10 cited
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