AUTALIC: A Dataset for Anti-AUTistic Ableist Language In Context

This publication is included in the Autistic Autism Scholarship Project. one author of this publication is identified as autistic in the project.

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Rizvi, N., Strickland, H., Gitelman, D., Flores, A. M., Cooper, T., Kallepalli, A., Alurkar, A., Owens, H., Ahmedi, S., Khirwadkar, I., Munyaka, I. N. S., & Ousidhoum, N. (2025). AUTALIC: A Dataset for Anti-AUTistic Ableist Language In Context. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 20999-21015. https://doi.org/10.18653/v1/2025.acl-long.1022

Publication date: 1 Jan 2025 Added to AutiHub: 21 Oct 2026 Type: Other Article language: English
Publisher source (DOI) Full text OpenAlex source

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Authors

Publication authors
12
Publication authors identified as autistic
1 / 12 (8.3%)
  1. Naba Rizvi *
  2. Harper Strickland
  3. Daniel Gitelman
  4. Alexis Morales Flores
  1. Tristan Cooper
  2. Aekta Kallepalli
  3. Akshat Alurkar
  4. Haaset Owens
  1. Saleha Ahmedi
  2. Isha Khirwadkar
  3. Imani N. S. Munyaka
  4. Nedjma Ousidhoum

Abstract

As our understanding of autism and ableism continues to increase, so does our understanding of ableist language towards autistic people. Such language poses a significant challenge in NLP research due to its subtle and context-dependent nature. Yet, detecting anti-autistic ableist language remains underexplored, with existing NLP tools often failing to capture its nuanced expressions. We present AUTALIC, the first benchmark dataset dedicated to the detection of anti-autistic ableist language in context, addressing a significant gap in the field. The dataset comprises 2,400 autism-related sentences collected from Reddit, accompanied by surrounding context, and is annotated by trained experts with backgrounds in neurodiversity. Our comprehensive evaluation reveals that current language models, including state-of-the-art LLMs, struggle to reliably identify anti-autistic ableism and align with human judgments, underscoring their limitations in this domain. We publicly release AUTALIC along with the individual annotations which serve as a valuable resource to researchers working on ableism, neurodiversity, and also studying disagreements in annotation tasks. This dataset serves as a crucial step towards developing more inclusive and context-aware NLP systems that better reflect diverse perspectives.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 28 Oct 2026 01:01.

Cited references
20
With a DOI
20
Without a DOI, from raw bibliography text
0
4 / 20 (20.0%) cited references include at least one author identified as autistic.
References with data to complete
0 / 20 (0.0%)
References with detected author names
20 / 20 (100.0%)
Without detected author names
0
Without a structured title
0
Without a stable identifier
0
References with raw author names still to review
0
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
85
From DOI or external metadata
85
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
0
22 / 85 (25.9%) names are linked to an author already present in AutiHub. 63 / 85 (74.1%) names are not yet linked.
Names linked to a person identified as autistic
4 / 85 (4.7%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 4 / 22 (18.2%). Distinct people identified as autistic: 3 / 82 (3.7%).
  1. Tolga Buz , Benjamin Frost , Nikola Genchev , Moritz Schneider , Lucie-Aimée Kaffee , Gerard de Melo (2024). Investigating Wit, Creativity, and Detectability of Large Language Models in Domain-Specific Writing Style Adaptation of Reddit’s Showerthoughts . Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), 291-307. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2024.starsem-1.23
    OpenCitations
  2. Maria Antoniak , Joel Mire , Maarten Sap , Elliott Ash , Andrew Piper (2024). Where Do People Tell Stories Online? Story Detection Across Online Communities . Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 7104-7130. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2024.acl-long.383
    OpenCitations
  3. Barbara Plank (2022). The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation . Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 10671-10682. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2022.emnlp-main.731
    OpenCitations
  4. Angeliki Sideraki , Athanasios Drigas (2021). Artificial Intelligence (AI) in Autism . Technium Social Sciences Journal, 26, 262-277. PLUS COMMUNICATION CONSULTING SRL.
    Type: Article DOI: 10.47577/tssj.v26i1.5208
    OpenCitations
  5. Panagiota Anagnostopoulou , Vasiliki Alexandropoulou , Georgia Lorentzou , Andriana Lykothanasi , Polyxeni Ntaountaki , Athanasios Drigas (2020). Artificial Intelligence in Autism Assessment . International Journal of Emerging Technologies in Learning (iJET), 15(06), 95. International Association of Online Engineering (IAOE).
    Type: Article DOI: 10.3991/ijet.v15i06.11231
    OpenCitations
  6. Aida Mostafazadeh Davani , Mohammad Atari , Brendan Kennedy , Morteza Dehghani (2023). Hate Speech Classifiers Learn Normative Social Stereotypes . Transactions of the Association for Computational Linguistics, 11, 300-319. MIT Press.
    Type: Article DOI: 10.1162/tacl_a_00550 OpenAlex: https://openalex.org/W4328051875
    OpenCitations
  8. Melissa Anderson-Chavarria (2022). The autism predicament: models of autism and their impact on autistic identity . Disability & Society, 37(8), 1321-1341. Informa UK Limited.
    Type: Article DOI: 10.1080/09687599.2021.1877117 OpenAlex: https://openalex.org/W3133441695
    OpenCitations
  10. Cella M Sum , Rahaf Alharbi , Franchesca Spektor , Cynthia L Bennett , Christina N Harrington , Katta Spiel et al. (2022). Dreaming Disability Justice in HCI . CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1-5. ACM.
    Type: Other DOI: 10.1145/3491101.3503731 OpenAlex: https://openalex.org/W4225156823
    OpenCitations
  11. Michael Yoder , Lynnette Ng , David West Brown , Kathleen Carley (2022). How Hate Speech Varies by Target Identity: A Computational Analysis . Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL), 27-39. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2022.conll-1.3 OpenAlex: https://openalex.org/W4385573162
    OpenCitations
  12. Keighley Overbay , Jaewoo Ahn , Fatemeh Pesaran zadeh , Joonsuk Park , Gunhee Kim (2023). mRedditSum: A Multimodal Abstractive Summarization Dataset of Reddit Threads with Images . Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 4117-4132. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2023.emnlp-main.251
    OpenCitations
  14. Vinitha Gadiraju , Shaun Kane , Sunipa Dev , Alex Taylor , Ding Wang , Remi Denton et al. (2023). "I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models . 2023 ACM Conference on Fairness Accountability and Transparency, 205-216. ACM.
    Type: Other DOI: 10.1145/3593013.3593989 OpenAlex: https://openalex.org/W4380319170
    OpenCitations
  15. Katta Spiel , Christopher Frauenberger , Os Keyes , Geraldine Fitzpatrick (2019). Agency of Autistic Children in Technology Research—A Critical Literature Review . ACM Transactions on Computer-Human Interaction, 26(6), 1-40. Association for Computing Machinery (ACM).
    Type: Article DOI: 10.1145/3344919 OpenAlex: https://openalex.org/W2988620880
    OpenCitations
  16. Ben Hutchinson , Vinodkumar Prabhakaran , Emily Denton , Kellie Webster , Yu Zhong , Stephen Denuyl (2020). Social Biases in NLP Models as Barriers for Persons with Disabilities . Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 5491-5501. Association for Computational Linguistics.
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    OpenCitations
  17. Min Su Park , Eunil Park (2023). ACL TA-DA: A Dataset for Text Summarization and Generation . Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 1233-1239. ACM.
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    OpenCitations
  18. Somin Wadhwa , Vivek Khetan , Silvio Amir , Byron Wallace (2023). RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media . Findings of the Association for Computational Linguistics: EACL 2023, 809-827. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2023.findings-eacl.61
    OpenCitations
  20. Pranav Narayanan Venkit , Mukund Srinath , Shomir Wilson (2023). Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models . Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023), 26-34. Association for Computational Linguistics.
    Type: Other DOI: 10.18653/v1/2023.trustnlp-1.3 OpenAlex: https://openalex.org/W4385734190
    OpenCitations