[2305.01633] Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
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arXiv:2305.01633 (cs)
[Submitted on 2 May 2023 (v1), last revised 7 Aug 2023 (this version, v2)]

Title:Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP

Authors: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
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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.
Comments: 5 pages plus appendix, 4 tables, 1 figure. To appear at "Workshop on Insights from Negative Results in NLP" (co-located with EACL2023). Updated author list and acknowledgements
Subjects: Computation and Language (cs.CL)
MSC classes: 68
ACM classes: I.2.7
Cite as: arXiv:2305.01633 [cs.CL]
  (or arXiv:2305.01633v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2305.01633

Submission history

From: Craig Thomson [view email]
[v1] Tue, 2 May 2023 17:46:12 UTC (35 KB)
[v2] Mon, 7 Aug 2023 09:54:55 UTC (35 KB)
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