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This repository accompanies the paper: Hechtner, F., Schmidt, L., Seebeck, A., & Weiß, M. (2025). How to design and employ specialized large language models for accounting and tax research: The example of TaxBERT.
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TaxBERT is a domain-adapated RoBERTa model, specifically designed to analyze qualitative corporate tax disclosures.
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**SSRN**: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5146523
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The paper provides an ‘A-to-Z’ description of how to design and employ specialized Bidirectional Encoder Representation of Transformers (BERT) models that are environmentally sustainable and practically feasible for accounting and tax researchers.
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This repository accompanies the paper: Hechtner, F., Schmidt, L., Seebeck, A., & Weiß, M. (2025). How to design and employ specialized large language models for accounting and tax research: The example of TaxBERT.
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TaxBERT is a domain-adapated RoBERTa model, specifically designed to analyze qualitative corporate tax disclosures.
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In the future, we will add the following features:
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- Tax Sentence Recognition
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- Tax Risk Sentiment
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**SSRN**: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5146523
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The paper provides an ‘A-to-Z’ description of how to design and employ specialized Bidirectional Encoder Representation of Transformers (BERT) models that are environmentally sustainable and practically feasible for accounting and tax researchers.
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