@inproceedings{thaepprasit-etal-2026-limits,
title = "What Limits Us? Analyzing Self-Reported Limitations in {NLP} Research",
author = "Thaepprasit, Tawan and
Kehasukcharoen, Peeranuth and
Wang, Ding and
Denton, Remi and
Vateekul, Peerapon and
Lertvittayakumjorn, Piyawat",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2026",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-emnlp.2386/",
pages = "51260--51297",
ISBN = "979-8-89176-462-0",
abstract = "Since late 2022, a Limitations section has become mandatory at many top-tier NLP conferences. The growing number of accepted papers at these venues has resulted in a vast corpus of self-reported limitations that cannot all be manually reviewed, yet remains systematically unanalyzed. Therefore, in this paper, we conduct a large-scale analysis of the Limitations sections from ACL and EMNLP papers published between 2020 and 2025 to understand what researchers disclose about their own work. To do so, we implement a novel human-AI framework for iterative hybrid qualitative coding. This framework enables us to investigate trends in self-reported limitations over time, their correlations with specific paper attributes, and the writing patterns that recur around these disclosures. Our findings offer a critical reflection on the diverse reported challenges as well as the self-reporting practices of researchers in the NLP community."
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%0 Conference Proceedings
%T What Limits Us? Analyzing Self-Reported Limitations in NLP Research
%A Thaepprasit, Tawan
%A Kehasukcharoen, Peeranuth
%A Wang, Ding
%A Denton, Remi
%A Vateekul, Peerapon
%A Lertvittayakumjorn, Piyawat
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Findings of the Association for Computational Linguistics: EMNLP 2026
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-462-0
%F thaepprasit-etal-2026-limits
%X Since late 2022, a Limitations section has become mandatory at many top-tier NLP conferences. The growing number of accepted papers at these venues has resulted in a vast corpus of self-reported limitations that cannot all be manually reviewed, yet remains systematically unanalyzed. Therefore, in this paper, we conduct a large-scale analysis of the Limitations sections from ACL and EMNLP papers published between 2020 and 2025 to understand what researchers disclose about their own work. To do so, we implement a novel human-AI framework for iterative hybrid qualitative coding. This framework enables us to investigate trends in self-reported limitations over time, their correlations with specific paper attributes, and the writing patterns that recur around these disclosures. Our findings offer a critical reflection on the diverse reported challenges as well as the self-reporting practices of researchers in the NLP community.
%U https://aclanthology.org/2026.findings-emnlp.2386/
%P 51260-51297
Markdown (Informal)
[What Limits Us? Analyzing Self-Reported Limitations in NLP Research](https://aclanthology.org/2026.findings-emnlp.2386/) (Thaepprasit et al., Findings 2026)
ACL
- Tawan Thaepprasit, Peeranuth Kehasukcharoen, Ding Wang, Remi Denton, Peerapon Vateekul, and Piyawat Lertvittayakumjorn. 2026. What Limits Us? Analyzing Self-Reported Limitations in NLP Research. In Findings of the Association for Computational Linguistics: EMNLP 2026, pages 51260–51297, Budapest, Hungary. Association for Computational Linguistics.