Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T13:06:13.618276Z
Paper Citation Record · LEDGER
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models
As of 19 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2509.00963.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
20 of 20 outbound references displayed
- verified exact1
- verified fuzzy7
- unresolved8
- parse uncertain2
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation aebb348f-bfef-47f2-9983-3b194cf8db7d · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T13:06:15.344533Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 38afddc2-9a64-41a9-be10-eb29fd2d4896 · outbound
This paper cites People with vision impairments exist.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models People with vision impairments exist
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:15.182631Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 9f0a6531-4b56-4560-97f2-89630bef0a34 · outbound
This paper cites In Proceedings of the 4th Interna- tional Workshop on Knowledge-Augmented Methods for Natural Language Processing, pages 215–229.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models In Proceedings of the 4th Interna- tional Workshop on Knowledge-Augmented Methods for Natural Language Processing, pages 215–229
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:16.773402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation dfccb1f9-98a3-459f-8c59-52bcda47b11d · outbound
This paper cites cold, calculated, and condescending.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models cold, calculated, and condescending
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:16.518866Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 48f03624-adff-4ad4-8c7e-2f50f32e0fac · outbound
This paper cites Beyond Keywords: Evaluating Large Language Model Classification of Nuanced Ableism.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Beyond Keywords: Evaluating Large Language Model Classification of Nuanced Ableism
Reference 5
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T13:06:13.860252Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 093e8fca-3ee7-4782-8476-37b7adf8c7c4 · outbound
This paper cites Human or LLM? A Comparative Study on Accessible Code Generation Capability.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Human or LLM? A Comparative Study on Accessible Code Generation Capability
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T13:06:13.740821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 51595d5d-3ef2-48af-ba4a-d98cd83edbc0 · outbound
This paper cites Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:06:12.875186Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63e4ebab-8432-4e80-9b27-5cd047fbd827 · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 9
- Resolution
- parse uncertain
- raw_fallback, observed 2026-08-05T13:06:16.288114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 128f8ef7-4d6e-421c-a4c9-7ce9c3e87f1f · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 10
- Resolution
- parse uncertain
- raw_fallback, observed 2026-08-05T13:06:16.083679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d4a483e3-a5c1-4064-b994-e1fa3afb0323 · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T13:06:15.867040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation dde0f03b-9711-42df-bba3-1fbb665b9621 · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T13:06:15.741402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 818fe025-33f4-4649-a5cb-dd0f806cdc41 · outbound
This paper cites Not applicable.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Not applicable
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:15.535942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6222f3d0-3cdb-4217-b547-bbda6dff57a5 · outbound
This paper cites Vision impairments may require screen readers.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Vision impairments may require screen readers
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:14.984819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a9b3daab-4c38-43e2-835e-9997a2237691 · outbound
This paper cites People with vision impairments may rely on screen readers, braille devices, tactile maps, or high-contrast displays.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models People with vision impairments may rely on screen readers, braille devices, tactile maps, or high-contrast displays
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:14.761186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b33e1cbd-c8d3-409b-a18a-f5c921464ef2 · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T13:06:14.578895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 253ee8ed-880b-4ebf-bfed-6df5a4c9c60c · outbound
This paper cites an unresolved cited work.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Unresolved cited work
Reference 19
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T13:06:14.409107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f7cba504-294d-4ebe-afc9-c98674385073 · outbound
This paper cites Input Template: Question: ##Question## Figure 4: Accessibility-aware response generation prompt A.3 Depth Results at 0, 1, 2.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Input Template: Question: ##Question## Figure 4: Accessibility-aware response generation prompt A.3 Depth Results at 0, 1, 2
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:06:14.222904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e1c3177f-9c5b-456c-a652-9d315def7e6e · outbound
This paper cites Sociodemographic Prompting is Not Yet an Effective Approach for Simulating Subjective Judgments with LLMs.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Sociodemographic Prompting is Not Yet an Effective Approach for Simulating Subjective Judgments with LLMs
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:06:12.808963Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b35a536-c347-48da-bd27-4be22b8560d2 · outbound
This paper cites Biased or Flawed? Mitigating Stereotypes in Generative Language Models by Addressing Task-Specific Flaws.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Biased or Flawed? Mitigating Stereotypes in Generative Language Models by Addressing Task-Specific Flaws
Reference 2024
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T13:06:14.018913Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f84eb83c-1c0d-4d36-a856-ad0d95758902 · outbound
This paper cites Social Biases in NLP Models as Barriers for Persons with Disabilities.
Who Gets Left Behind? Auditing Disability Inclusivity in Large Language Models Social Biases in NLP Models as Barriers for Persons with Disabilities
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:06:12.539684Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.