Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally
Published in NeurIPS, 2025
The World Central Banks (WCB) paper introduces the most comprehensive dataset of central bank communications to date, spanning 380k+ sentences from 25 central banks across 28 years. It includes expert-annotated labels for stance detection (hawkish/dovish/neutral), temporal classification, and uncertainty estimation, designed to evaluate both pretrained and large language models in high-stakes financial policy contexts.
Key highlights:
- Benchmarked 15k+ experiments across state-of-the-art NLP models, including large language models.
- Demonstrated that cross-bank training yields significantly better performance than single-bank training.
- Released the WCB dataset, along with scripts and evaluation pipelines, to support further research on monetary policy and financial NLP.
† Indicates core contributors.
Recommended citation: Agam Shah, Siddhant Sukhani, Huzaifa Pardawala, Saketh Budideti†, Riya Bhadani†, Rudra Gopal†, Siddhartha Somani†, Michael Galarnyk†, Soungmin Lee†, et al. (2025). "Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally." NeurIPS 2025.
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