- Do, S., Ollion, É., & Shen, R. (2022). The Augmented Social Scientist: Using Sequential Transfer Learning to Annotate Millions of Texts with Human-Level Accuracy. Sociological Methods & Research, https://doi.org/10.1177/00491241221134526.
- Ted Underwood. 2023. ‘Using GPT-4 to measure the passage of time in fiction’. Code at https://github.com/tedunderwood/fictional-time-with-GPT4/tree/main.
- Andres Karjus. 2023. “Machine-Assisted Mixed Methods: Augmenting Humanities and Social Sciences with Artificial Intelligence.” arXiv, September 24, 2023. http://arxiv.org/abs/2309.14379.
- Wang et al. 2023. On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective. https://arxiv.org/abs/2302.12095
- Rathkopf, Charles, and Bert Heinrichs. 2023. ‘Learning to Live with Strange Error: Beyond Trustworthiness in Artificial Intelligence Ethics’. Cambridge Quarterly of Healthcare Ethics, January, 1–13. https://doi.org/10.1017/S0963180122000688.
- Maya Akim. 2023. Complete Guide to LLM Fine Tuning for Beginners, https://medium.com/@mayaakim/complete-guide-to-llm-fine-tuning-for-beginners-c2c38a3252be
- Google Colab Notebook for calculating interrater reliability scores.
- Jupyter Notebook for running LLMs locally with Ollama.