Software and data underlying the publication: "Natural Language Counterfactual Explanations in Financial Text Classification: A Comparison of Generators and Evaluation Metrics"
DOI: 10.4121/7270e8b5-134a-4939-b614-158a7d225622
Datacite citation style
Dataset
Licence MIT
Interoperability
This dataset contains the data collected through experiments, surveys, and analyzed results obtained for the ACL GEM^2 2025 workshop submission titled Natural Language Counterfactual Explanations in Financial Text Classification: A Comparison of Generators and Evaluation Metrics. This project aimed to use texts from expert domains in order to evaluate state-of-the-art methods for generating text counterfactual explanations for large language model text classification. The data contains pre-processed texts from a financial dataset "Trillion Dollar Words", the counterfactuals generated in the experiments, as well raw and pre-processed results of the metric-based and human annotation-based experiments. Additionally, we include the software used in generating our results.
History
- 2025-11-18 first online, published, posted
Publisher
4TU.ResearchDataFormat
.zip compressed catalogs containing .csv and .json data files, and .ipynb software filesReferences
Organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent SystemsDATA
Files (2)
- 7,719,961 bytesMD5:
cb745f0256bb21dd67b1517ded6bf04dARR_submission_data.zip - 7,120,465 bytesMD5:
d9a337a210e26bdca624fdaa4736be84ARR_submission_software.zip -
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