A five-day intensive for early-career social scientists working with language models.
Mornings: technical lectures from ML practitioners and invited researchers. Afternoons: hands-on labs and a week-long collaborative research project. Tuition is free for all admitted participants.
A participant-to-co-author pipeline.
The school is designed around a participant-to-co-author pipeline. Collaborative projects begun during the week continue beyond it: in 2025, a team of participants and speakers submitted a joint paper for peer review.
30 researchers. A prediction competition. One paper submitted.
Lectures on LLM fundamentals, evaluation, fine-tuning, AI agents, and AI safety. A Kaggle-style prediction competition ran alongside the research project. A team of participants and speakers continued the work after September and submitted it for peer review.
Read the 2025 report →
30 participants from ~200 applications.
Applied tutorials on RAG, observability, and agent-based systems. A cross-discipline line-up of NLP engineers, social scientists, and practitioners from Qdrant, Ori Cloud, Arize, and Google.
Read the 2024 report →
The first Oxford LLMs workshop.
Convened by Elena Voita and Ilya Boytsov for a cohort of ~30 early-career researchers exploring transformers, text-as-data methods, and the emerging landscape of large language models.
Read the 2023 report →
Slides and notebooks from past editions.
All lecture slides and coding materials are published openly after each edition. Datasets and model checkpoints from collaborative research projects are on Hugging Face.
Slides, notebooks & datasets
Slides, notebooks & datasets
Materials are being uploaded and will appear here shortly.