---
title: "FinQA / ConvFinQA / TAT-QA: papers using it"
description: "From Nov 2023 to Oct 2026, 14 archived papers mentioned FinQA / ConvFinQA / TAT-QA in their title, abstract, keywords or full text, most of them in Feb 2026 (2)."
url: https://scholar4ai.com/datasets/finqa-convfinqa-tat-qa
markdown_url: https://scholar4ai.com/datasets/finqa-convfinqa-tat-qa.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From Nov 2023 to Oct 2026, 14 archived papers mentioned FinQA / ConvFinQA / TAT-QA in their title, abstract, keywords or full text, most of them in Feb 2026 (2). (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# FinQA / ConvFinQA / TAT-QA

[Browse dataset profiles](https://scholar4ai.com/datasets/directory/page/3.md)

Labelled financial texts used to train and test language models on finance.

- data category: Financial NLP datasets
- 0 papers in the last 7 days
- Names searched for: FinQA, ConvFinQA, TAT-QA

Most-used data: https://scholar4ai.com/rankings/datasets.md · All Financial NLP datasets datasets: https://scholar4ai.com/datasets/financial-nlp-datasets.md



## Key findings

- From Nov 2023 to Oct 2026, 14 archived papers mentioned FinQA / ConvFinQA / TAT-QA in their title, abstract, keywords or full text, most of them in Feb 2026 (2).
- FinQA / ConvFinQA / TAT-QA was mentioned in 1 paper in the last 30 days (2026-10-07 to 2026-11-05), ranking #165 of the 246 datasets mentioned.
- By journal category: AI (1).
- Most of them appeared in Artificial Intelligence Review (1).
- From 2017 to 2026 (so far), FinQA / ConvFinQA / TAT-QA was mentioned in 14 papers in the tracked journals, most of them in AI (10), information systems (2) and economics (1).
- 5 of them were published in 2025, against 0 in 2017.
- Since 2023, the institutions with the most of these papers were The University of Melbourne (3), The University of Sydney (2) and Tsinghua University (2).
- The journals publishing most of them were Artificial Intelligence Review (2), Neural Computing and Applications (2) and Knowledge-Based Systems (2).
- The most-cited of them is “AI for social science and social science of AI: A survey” (Information Processing & Management, 2024), with 126 citations.
- Papers use FinQA / ConvFinQA / TAT-QA most often with Wikipedia (9), FiQA (4) and Twitter / X (4); it has 4 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok.

## Mentions over 36 months

*Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts, keywords and full texts)*

| Trend | Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---|---:|---:|---:|---:|
|  | 3 | 5 | 6 | 14 |

## Papers per year

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | 5 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
| [Economics](https://scholar4ai.com/categories/economics.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| All categories | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | 6 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2 |
| 2 | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 |
| 3 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2 |
| 4 | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | 2 |
| 5 | [World Wide Web](https://scholar4ai.com/journals/world-wide-web.md) | 2 |
| 6 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 1 |
| 7 | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | 1 |
| 8 | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | 1 |
| 9 | [Computational Economics](https://scholar4ai.com/journals/computational-economics.md) | 1 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [The University of Melbourne](https://scholar4ai.com/institutions/the-university-of-melbourne.md) | 3 |
| 2 | [The University of Sydney](https://scholar4ai.com/institutions/the-university-of-sydney.md) | 2 |
| 3 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 2 |
| 4 | [UNSW Sydney](https://scholar4ai.com/institutions/unsw-sydney.md) | 2 |
| 5 | [Aalto University](https://scholar4ai.com/institutions/aalto-university.md) | 1 |
| 6 | BASF (Germany) | 1 |
| 7 | [Beijing Institute of Technology](https://scholar4ai.com/institutions/beijing-institute-of-technology.md) | 1 |
| 8 | [Centre National de la Recherche Scientifique](https://scholar4ai.com/institutions/centre-national-de-la-recherche-scientifique.md) | 1 |
| 9 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 1 |
| 10 | DELL (United States) | 1 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 5 |
| 2 | Australia | 4 |
| 3 | Belgium | 1 |
| 4 | Brazil | 1 |
| 5 | Switzerland | 1 |
| 6 | Germany | 1 |
| 7 | Finland | 1 |
| 8 | France | 1 |
| 9 | India | 1 |
| 10 | Singapore | 1 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 7 |
| 2 | [feature fusion](https://scholar4ai.com/keywords/feature-fusion.md) | 2 |
| 3 | open-ended question answering | 2 |
| 4 | pre-trained language models | 2 |
| 5 | tabular data | 2 |
| 6 | AI agents | 1 |
| 7 | AI-assisted research | 1 |
| 8 | [BERT](https://scholar4ai.com/keywords/bert.md) | 1 |
| 9 | CNN feature extraction | 1 |
| 10 | GPT | 1 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 126 | 3.8 | [AI for social science and social science of AI: A survey](https://doi.org/10.1016/j.ipm.2024.103665) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | 2024-02-08 | R. F. Xu, Yingfei Sun, Mengjie Ren et al. |
| 2 | 85 | 3.9 | [Large Language Models in Finance (FinLLMs)](https://doi.org/10.1007/s00521-024-10495-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2025-01-11 | Jean Lee, Nicholas Stevens, Soyeon Caren Han |
| 3 | 72 | 3.8 | [A comprehensive survey on integrating large language models with knowledge-based methods](https://doi.org/10.1016/j.knosys.2025.113503) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2025-04-12 | Wenli Yang, Lilian Some, Michael Bain et al. |
| 4 | 28 | 1.3 | [Integration of CNN Models and Machine Learning Methods in Credit Score Classification: 2D Image Transformation and Feature Extraction](https://doi.org/10.1007/s10614-025-10893-5) | [Computational Economics](https://scholar4ai.com/journals/computational-economics.md) | 2025-02-05 | Yunus Emre Gür, Mesut Toğaçar, Bilal Solak |
| 5 | 21 | 1.4 | [Demystifying Chains, Trees, and Graphs of Thoughts](https://doi.org/10.1109/tpami.2025.3598182) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2025-08-12 | Maciej Besta, Florim Memedi, Zhenyu Zhang et al. |

## Used together with

Papers use FinQA / ConvFinQA / TAT-QA most often with Wikipedia (9), FiQA (4) and Twitter / X (4); it has 4 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok.

*What papers use FinQA / ConvFinQA / TAT-QA together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [Wikipedia](https://scholar4ai.com/datasets/wikipedia.md) | Dataset | 9 | 30.3 |
| [FiQA](https://scholar4ai.com/datasets/fiqa.md) | Dataset | 4 | 683.4 |
| [Twitter / X](https://scholar4ai.com/datasets/twitter-x.md) | Dataset | 4 | 3.1 |
| [Financial PhraseBank](https://scholar4ai.com/datasets/financial-phrasebank.md) | Dataset | 3 | 512.6 |

The whole network: https://scholar4ai.com/code/network.md

## Papers

*Papers mentioning FinQA / ConvFinQA / TAT-QA in the last 30 days, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-17 | [Language modeling on tabular data: a survey of foundations, techniques and evolution](https://doi.org/10.1007/s10462-026-11726-z) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Yucheng Ruan, Xiang Lan, Jingying Ma et al. | National University of Singapore; Institute of Data Science |

## Cite this page

Scholar4AI. (2026). FinQA / ConvFinQA / TAT-QA. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/finqa-convfinqa-tat-qa

```bibtex
@misc{scholar4ai-datasets-finqa-convfinqa-tat-qa,
  author = {{Scholar4AI}},
  title = {FinQA / ConvFinQA / TAT-QA},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/finqa-convfinqa-tat-qa}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).