Predicting COVID-19 Cases using Reddit Posts and other Online Resources (short paper). - Felix Drinkall; Janet B. Pierrehumbert (SwissText, 2021)

Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts. - Felix Drinkall; Stefan Zohren; Janet B. Pierrehumbert (NAACL-HLT, 2022)

Time Machine GPT. - Felix Drinkall; Eghbal Rahimikia; Janet B. Pierrehumbert; Stefan Zohren (NAACL-HLT (Findings), 2024)

Traditional Methods Outperform Generative LLMs at Forecasting Credit Ratings. - Felix Drinkall; Janet B. Pierrehumbert; Stefan Zohren (CoRR, 2024)

Language Models Learn Metadata: Political Stance Detection Case Study. - Stanley Cao; Felix Drinkall (CoRR, 2024)

Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups. - Felix Drinkall; Stefan Zohren; Michael McMahon; Janet B. Pierrehumbert (ACL (Findings), 2025)

Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs. - Felix Drinkall; Janet B. Pierrehumbert; Stefan Zohren (COLING Workshops, 2025)

Jailbreaking Large Language Models in Infinitely Many Ways. - Oliver Goldstein; Emanuele La Malfa; Felix Drinkall; Samuele Marro; Michael J. Wooldridge (CoRR, 2025)

When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks. - Felix Drinkall; Janet B. Pierrehumbert; Stefan Zohren (CoRR, 2025)