Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
Anya Belz, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose M. Alonso-Moral, Mohammad Arvan, Anouck Braggaar, Mark Cieliebak, Elizabeth Clark, Kees van Deemter, Tanvi Dinkar, Ondřej Dušek, Steffen Eger, Qixiang Fang, Mingqi Gao, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Manuela Hürlimann, Takumi Ito, John D. Kelleher, Filip Klubicka, Emiel Krahmer, Huiyuan Lai, Chris van der Lee, Yiru Li, Saad Mahamood, Margot Mieskes, Emiel van Miltenburg, Pablo Mosteiro, Malvina Nissim, Natalie Parde, Ondřej Plátek, Verena Rieser, Jie Ruan, Joel Tetreault, Antonio Toral, Xiaojun Wan, Leo Wanner, Lewis Watson, Diyi Yang
Correct Metadata for
Abstract
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible. We present our results and findings, which include that just 13% of papers had (i) sufficiently low barriers to reproduction, and (ii) enough obtainable information, to be considered for reproduction, and that all but one of the experiments we selected for reproduction was discovered to have flaws that made the meaningfulness of conducting a reproduction questionable. As a result, we had to change our coordinated study design from a reproduce approach to a standardise-then-reproduce-twice approach. Our overall (negative) finding that the great majority of human evaluations in NLP is not repeatable and/or not reproducible and/or too flawed to justify reproduction, paints a dire picture, but presents an opportunity for a rethink about how to design and report human evaluations in NLP.- Anthology ID:
- 2023.insights-1.1
- Original:
- 2023.insights-1.1v1
- Version 2:
- 2023.insights-1.1v2
- Volume:
- Proceedings of the Fourth Workshop on Insights from Negative Results in NLP
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Shabnam Tafreshi, Arjun Akula, João Sedoc, Aleksandr Drozd, Anna Rogers, Anna Rumshisky
- Venues:
- insights | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–10
- Language:
- URL:
- https://aclanthology.org/2023.insights-1.1/
- DOI:
- 10.18653/v1/2023.insights-1.1
- Bibkey:
- Cite (ACL):
- Anya Belz, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose M. Alonso-Moral, Mohammad Arvan, Anouck Braggaar, Mark Cieliebak, Elizabeth Clark, Kees van Deemter, Tanvi Dinkar, Ondřej Dušek, Steffen Eger, Qixiang Fang, Mingqi Gao, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Manuela Hürlimann, Takumi Ito, John D. Kelleher, Filip Klubicka, Emiel Krahmer, Huiyuan Lai, Chris van der Lee, Yiru Li, Saad Mahamood, Margot Mieskes, Emiel van Miltenburg, Pablo Mosteiro, Malvina Nissim, Natalie Parde, Ondřej Plátek, Verena Rieser, Jie Ruan, Joel Tetreault, Antonio Toral, Xiaojun Wan, Leo Wanner, Lewis Watson, and Diyi Yang. 2023. Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP. In Proceedings of the Fourth Workshop on Insights from Negative Results in NLP, pages 1–10, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP (Belz et al., insights 2023)
- Copy Citation:
- PDF:
- https://aclanthology.org/2023.insights-1.1.pdf
- Video:
- https://aclanthology.org/2023.insights-1.1.mp4
Export citation
@inproceedings{belz-etal-2023-missing,
title = "Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in {NLP}",
author = {Belz, Anya and
Thomson, Craig and
Reiter, Ehud and
Abercrombie, Gavin and
Alonso-Moral, Jose M. and
Arvan, Mohammad and
Braggaar, Anouck and
Cieliebak, Mark and
Clark, Elizabeth and
van Deemter, Kees and
Dinkar, Tanvi and
Du{\v{s}}ek, Ond{\v{r}}ej and
Eger, Steffen and
Fang, Qixiang and
Gao, Mingqi and
Gatt, Albert and
Gkatzia, Dimitra and
Gonz{\'a}lez-Corbelle, Javier and
Hovy, Dirk and
H{\"u}rlimann, Manuela and
Ito, Takumi and
Kelleher, John D. and
Klubicka, Filip and
Krahmer, Emiel and
Lai, Huiyuan and
van der Lee, Chris and
Li, Yiru and
Mahamood, Saad and
Mieskes, Margot and
van Miltenburg, Emiel and
Mosteiro, Pablo and
Nissim, Malvina and
Parde, Natalie and
Pl{\'a}tek, Ond{\v{r}}ej and
Rieser, Verena and
Ruan, Jie and
Tetreault, Joel and
Toral, Antonio and
Wan, Xiaojun and
Wanner, Leo and
Watson, Lewis and
Yang, Diyi},
editor = "Tafreshi, Shabnam and
Akula, Arjun and
Sedoc, Jo{\~a}o and
Drozd, Aleksandr and
Rogers, Anna and
Rumshisky, Anna",
booktitle = "Proceedings of the Fourth Workshop on Insights from Negative Results in NLP",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.insights-1.1/",
doi = "10.18653/v1/2023.insights-1.1",
pages = "1--10",
abstract = "We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible. We present our results and findings, which include that just 13{\%} of papers had (i) sufficiently low barriers to reproduction, and (ii) enough obtainable information, to be considered for reproduction, and that all but one of the experiments we selected for reproduction was discovered to have flaws that made the meaningfulness of conducting a reproduction questionable. As a result, we had to change our coordinated study design from a reproduce approach to a standardise-then-reproduce-twice approach. Our overall (negative) finding that the great majority of human evaluations in NLP is not repeatable and/or not reproducible and/or too flawed to justify reproduction, paints a dire picture, but presents an opportunity for a rethink about how to design and report human evaluations in NLP."
}
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%0 Conference Proceedings %T Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP %A Belz, Anya %A Thomson, Craig %A Reiter, Ehud %A Abercrombie, Gavin %A Alonso-Moral, Jose M. %A Arvan, Mohammad %A Braggaar, Anouck %A Cieliebak, Mark %A Clark, Elizabeth %A van Deemter, Kees %A Dinkar, Tanvi %A Dušek, Ondřej %A Eger, Steffen %A Fang, Qixiang %A Gao, Mingqi %A Gatt, Albert %A Gkatzia, Dimitra %A González-Corbelle, Javier %A Hovy, Dirk %A Hürlimann, Manuela %A Ito, Takumi %A Kelleher, John D. %A Klubicka, Filip %A Krahmer, Emiel %A Lai, Huiyuan %A van der Lee, Chris %A Li, Yiru %A Mahamood, Saad %A Mieskes, Margot %A van Miltenburg, Emiel %A Mosteiro, Pablo %A Nissim, Malvina %A Parde, Natalie %A Plátek, Ondřej %A Rieser, Verena %A Ruan, Jie %A Tetreault, Joel %A Toral, Antonio %A Wan, Xiaojun %A Wanner, Leo %A Watson, Lewis %A Yang, Diyi %Y Tafreshi, Shabnam %Y Akula, Arjun %Y Sedoc, João %Y Drozd, Aleksandr %Y Rogers, Anna %Y Rumshisky, Anna %S Proceedings of the Fourth Workshop on Insights from Negative Results in NLP %D 2023 %8 May %I Association for Computational Linguistics %C Dubrovnik, Croatia %F belz-etal-2023-missing %X We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible. We present our results and findings, which include that just 13% of papers had (i) sufficiently low barriers to reproduction, and (ii) enough obtainable information, to be considered for reproduction, and that all but one of the experiments we selected for reproduction was discovered to have flaws that made the meaningfulness of conducting a reproduction questionable. As a result, we had to change our coordinated study design from a reproduce approach to a standardise-then-reproduce-twice approach. Our overall (negative) finding that the great majority of human evaluations in NLP is not repeatable and/or not reproducible and/or too flawed to justify reproduction, paints a dire picture, but presents an opportunity for a rethink about how to design and report human evaluations in NLP. %R 10.18653/v1/2023.insights-1.1 %U https://aclanthology.org/2023.insights-1.1/ %U https://doi.org/10.18653/v1/2023.insights-1.1 %P 1-10
Markdown (Informal)
[Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP](https://aclanthology.org/2023.insights-1.1/) (Belz et al., insights 2023)
- Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP (Belz et al., insights 2023)
ACL
- Anya Belz, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose M. Alonso-Moral, Mohammad Arvan, Anouck Braggaar, Mark Cieliebak, Elizabeth Clark, Kees van Deemter, Tanvi Dinkar, Ondřej Dušek, Steffen Eger, Qixiang Fang, Mingqi Gao, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Manuela Hürlimann, Takumi Ito, John D. Kelleher, Filip Klubicka, Emiel Krahmer, Huiyuan Lai, Chris van der Lee, Yiru Li, Saad Mahamood, Margot Mieskes, Emiel van Miltenburg, Pablo Mosteiro, Malvina Nissim, Natalie Parde, Ondřej Plátek, Verena Rieser, Jie Ruan, Joel Tetreault, Antonio Toral, Xiaojun Wan, Leo Wanner, Lewis Watson, and Diyi Yang. 2023. Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP. In Proceedings of the Fourth Workshop on Insights from Negative Results in NLP, pages 1–10, Dubrovnik, Croatia. Association for Computational Linguistics.