1 citations · 2 across the 5 of their papers we have counts for
5 papers
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 +1
Macroeconomic fluctuations and the narratives that shape them form a mutually reinforcing cycle: public discourse can spur behavioural changes leading to economic shifts, which the…
When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks
Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
Large language models (LLMs) have shown remarkable success in language modelling due to scaling laws found in model size and the hidden dimension of the model's text representation…
Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs
Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
Large Language Models (LLMs) have been shown to perform well for many downstream tasks. Transfer learning can enable LLMs to acquire skills that were not targeted during pre-traini…
Time Machine GPT
Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert +1
Large language models (LLMs) are often trained on extensive, temporally indiscriminate text corpora, reflecting the lack of datasets with temporal metadata. This approach is not al…
Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts
Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert
We present a novel approach incorporating transformer-based language models into infectious disease modelling. Text-derived features are quantified by tracking high-density cluster…