---
license: mit
language:
- en
---
# TaxBERT

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.
TaxBERT is a domain-adapated RoBERTa model, specifically designed to analyze qualitative corporate tax disclosures.

In the future, we will add the following features:
- Tax Sentence Recognition
- Tax Risk Sentiment

**SSRN**: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5146523
          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.

**GitHub**: https://github.com/TaxBERT/TaxBERT

If the following Guide/Repository is used for academic or scientific purposes, please cite the paper.