Pith. sign in

REVIEW 2 cited by

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2410.16520 v4 pith:TR7U27F5 submitted 2024-10-21 cs.CL cs.AI

classification cs.CLcs.AI
keywords languageableistanti-autisticdatasetableismautaliccontextneurodiversity
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original 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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Beyond Keywords: Evaluating Large Language Model Classification of Nuanced Ableism

    cs.CL 2025-05 conditional novelty 7.0 of 10

    LLMs identify autism-related words but frequently misclassify nuanced ableism, over-flagging intra-community language and under-flagging harmful stereotypes.

  2. Beyond the Veil: Charting WIMP Territories at the Neutrino Floor

    hep-ph 2025-07 conditional novelty 4.0 of 10

    Freeze-in, early matter domination, and fast-expanding cosmologies keep many WIMP models within reach of next-generation direct detection experiments at the neutrino floor.

Pith tools