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paper/paper.bib

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@@ -145,6 +145,7 @@ @misc{kiritchenko2018examininggenderracebias
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/1805.04508},
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doi={10.18653/v1/S18-2005}
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}
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author={Samuel Gehman and Suchin Gururangan and Maarten Sap and Yejin Choi and Noah A. Smith},
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booktitle={Findings},
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year={2020},
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url={https://api.semanticscholar.org/CorpusID:221878771}
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url={https://api.semanticscholar.org/CorpusID:221878771},
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doi={10.18653/v1/2020.findings-emnlp.301}
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}
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eprint = {1907.04135},
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timestamp = {Wed, 17 Jul 2019 10:27:36 +0200},
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biburl = {https://dblp.org/rec/journals/corr/abs-1907-04135.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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bibsource = {dblp computer science bibliography, https://dblp.org},
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doi = {
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https://doi.org/10.1109/TVCG.2019.2934619}
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}
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@@ -515,6 +519,7 @@ @misc{huang2020reducingsentimentbiaslanguage
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/1911.03064},
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doi={10.18653/v1/2020.findings-emnlp.7}
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}
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archivePrefix={arXiv},
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primaryClass={stat.ML},
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url={https://arxiv.org/abs/1412.3756},
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doi={https://doi.org/10.1145/2783258.2783311}
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}
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@@ -552,6 +558,7 @@ @misc{goldfarbtarrant2021intrinsicbiasmetricscorrelate
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2012.15859},
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doi={10.18653/v1/2021.acl-long.150}
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}
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paper/paper.md

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@@ -46,7 +46,7 @@ Furthermore, LangFair is designed for real-world LLM-based systems that require
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# Generation of Evaluation Datasets
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The `langfair.generator` module offers two classes, `ResponseGenerator` and `CounterfactualGenerator`, which aim to enable user-friendly construction of evaluation datasets for text generation use cases.
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The `langfair.generator` module offers two classes, `ResponseGenerator` and `Counterfactual`-`Generator`, which aim to enable user-friendly construction of evaluation datasets for text generation use cases.
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### `ResponseGenerator` class

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