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Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups
Macroeconomic fluctuations and the narratives that shape them form a mutually reinforcing cycle: public discourse can spur behavioural …
Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
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Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs
Large Language Models (LLMs) have been shown to perform well for many downstream tasks. Transfer learning can enable LLMs to acquire …
Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
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Time Machine GPT
Large language models (LLMs) are often trained on extensive, temporally indiscriminate text corpora, reflecting the lack of datasets …
Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert, Stefan Zohren
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Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts
We present a novel approach incorporating transformer-based language models into infectious disease modelling. Text-derived features …
Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert
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