BIS paper explores ‘ChatGPT for central banking’
Language models can analyse sentences but needs more work when it comes to complex content
A domain-specific language model that parses central bank data has produced mixed results when it comes to predicting monetary policy stances, a Bank for International Settlements (BIS) study argues.
The working paper, published on October 1, looks at whether “central banking language models” (CB-LMs) can accurately assess sentiment from monetary policy statements.
Unlike large language models (LLMs) such as ChatGPT, CB-LMs are domain-specific. This means they are trained on data that exclusively
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