language:en license:mit size_categories:n<1K format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us aveni-bench question-answering finnlp
---
license: mit
language:
  - en
configs:
  - config_name: aveni-bench-finqa
    data_files:
      - split: test
        path:
          - data/test.jsonl
    default: true
tags:
    - aveni-bench
    - question-answering
    - finnlp
---
# AveniBench: FinQA

FinQA split used in the AveniBench.

## License

This dataset is made available under the MIT license.

## Citation

AveniBench
```bibtex
TDB
```

FinQA
```bibtex
@inproceedings{chen-etal-2021-finqa,
    title = "{F}in{QA}: A Dataset of Numerical Reasoning over Financial Data",
    author = "Chen, Zhiyu  and
      Chen, Wenhu  and
      Smiley, Charese  and
      Shah, Sameena  and
      Borova, Iana  and
      Langdon, Dylan  and
      Moussa, Reema  and
      Beane, Matt  and
      Huang, Ting-Hao  and
      Routledge, Bryan  and
      Wang, William Yang",
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2021",
    address = "Online and Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.emnlp-main.300/",
    doi = "10.18653/v1/2021.emnlp-main.300",
    pages = "3697--3711",
}
```

ConvFinQA
```bibtex
@inproceedings{chen-etal-2022-convfinqa,
    title = "{C}onv{F}in{QA}: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering",
    author = "Chen, Zhiyu  and
      Li, Shiyang  and
      Smiley, Charese  and
      Ma, Zhiqiang  and
      Shah, Sameena  and
      Wang, William Yang",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.emnlp-main.421/",
    doi = "10.18653/v1/2022.emnlp-main.421",
    pages = "6279--6292",
}
```
