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Paper Citation Record · LEDGER

Are Large Language Models the future crowd workers of Linguistics?

As of 9 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2502.10266.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.10266 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:47:07.133196Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved8
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8bfb784-2b8c-49f1-b4c8-208003715bf7 · outbound

This paper cites Design and evaluation of crowdsourcing platforms based on users’ confidence judgments.

Are Large Language Models the future crowd workers of Linguistics? Design and evaluation of crowdsourcing platforms based on users’ confidence judgments

Reference 1

Resolution
malformed identifier
no resolver link, observed 2026-08-07T18:47:07.084948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.084948Z digest=sha256:17ae03323e4b6c6c629d33e86c7c23075c40dd56b946aa27685f831cc7ceb555

Observation b8b746e2-6b15-4844-b1a1-2b813d5f469f · outbound

This paper cites The challenge of using LLMs to simulate human behavior: A causal inference perspective.

Are Large Language Models the future crowd workers of Linguistics? The challenge of using LLMs to simulate human behavior: A causal inference perspective

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.093921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.093921Z digest=sha256:fdd9c605297dfc22f2441354de84562a70aed9c5a2302347fcfe2d81c9830411

Observation 04192d8f-6975-4641-ab55-890679b3b63f · outbound

This paper cites On the role of large language models in crowdsourcing misinformation assessment.

Are Large Language Models the future crowd workers of Linguistics? On the role of large language models in crowdsourcing misinformation assessment

Reference 3

Resolution
verified exact
doi, observed 2026-08-07T18:47:07.171802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T18:47:07.129215Z digest=sha256:ba7de9c2e067b3885a4b205cc4687be06999b89ee64f23e92d9e287c8ad83e2c

Observation e0519ee4-f30a-4aa0-8d49-322c335e1070 · outbound

This paper cites AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators.

Are Large Language Models the future crowd workers of Linguistics? AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.097975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.097975Z digest=sha256:21ecf12cf8a244764f46470d90f2913f41d310ed109331f0dd3da6ff57370693

Observation 1df8bac3-7cfb-4be6-852d-24257bd48bd2 · outbound

This paper cites The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection.

Are Large Language Models the future crowd workers of Linguistics? The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.102184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.102184Z digest=sha256:ff5738eb569e98f16467debba4c5ddbf479bd6bcfa41f8bba896fe2f7480a511

Observation 111734b8-9cad-48ca-a4e7-94b807c1066c · outbound

This paper cites ChatGPT vs.

Are Large Language Models the future crowd workers of Linguistics? ChatGPT vs

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.118268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.118268Z digest=sha256:92e13053091147ddb8a5d1e230082ec9b18dfd85eb44beaffb77cd6e410a3e6e

Observation bf7a26aa-8ce5-4bb1-ae21-95903756f74b · outbound

This paper cites Crowdsourc- ing lexical diversity.

Are Large Language Models the future crowd workers of Linguistics? Crowdsourc- ing lexical diversity

Reference 7

Resolution
verified exact
raw_fallback, observed 2026-08-07T18:47:07.583374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T18:47:07.111034Z digest=sha256:bbf8843d8bab2d9984a5bd34b4124f3e5a7b06e6013ea64505cda8a40ac8fb86

Observation 64278b1a-3dce-4280-a938-eb667e882836 · outbound

This paper cites ChatGPT: Jack of all trades, master of none.

Are Large Language Models the future crowd workers of Linguistics? ChatGPT: Jack of all trades, master of none

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.114839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.114839Z digest=sha256:a52f2defa0332923aedcb48268f20fa9260215b3e344038d14cfb96edbe8141c

Observation e2298459-5aa5-45cc-a6d2-0587155b04be · outbound

This paper cites Direct and indirect annotation with generative AI: A case study into finding animals and plants in historical text.

Are Large Language Models the future crowd workers of Linguistics? Direct and indirect annotation with generative AI: A case study into finding animals and plants in historical text

Reference 10

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T18:47:07.373657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T18:47:07.121572Z digest=sha256:a3615cf57d82ec42ad5bf94c8efd8c8a45bea5d210f05e1a2d41c5f36b1ba45c

Observation d89d0167-ab84-4944-822d-e4a461a9660d · outbound

This paper cites LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs.

Are Large Language Models the future crowd workers of Linguistics? LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.125085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.125085Z digest=sha256:73c7f67b177c1d74aa89cb2ff9cb98b1a62f39cec1b3acfcf8f143ac5cbb33cc

Observation b64532d1-aad2-43ea-9b5a-c21d8987fa30 · outbound

This paper cites doi:10.1017/pan.2023.2.

Are Large Language Models the future crowd workers of Linguistics? doi:10.1017/pan.2023.2

Reference 2023

Resolution
verified exact
raw_fallback, observed 2026-08-07T18:47:07.690514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T18:47:07.089185Z digest=sha256:9885f8455e021f8a31ef9782184fb4a4344d509c35d623e4c820d4805a75bdfa

Observation 1d51aa29-d65f-4b58-879f-aceb71a39baf · outbound

This paper cites Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence.

Are Large Language Models the future crowd workers of Linguistics? Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.106548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.106548Z digest=sha256:0d210e9eed5ba641ceb53861f98b61ea596f9cded151b03e5427a1eb8d8d62f6

Observation 92c0cf15-3300-4fe1-88c6-f4c439b63762 · outbound

This paper cites URL https://direct.mit.edu/coli/article/50/1/237/118498/ Can-Large-Language-Models-Transform-Computational.

Are Large Language Models the future crowd workers of Linguistics? URL https://direct.mit.edu/coli/article/50/1/237/118498/ Can-Large-Language-Models-Transform-Computational

Reference 9312

Resolution
unresolved
no resolver link, observed 2026-08-07T18:47:07.133196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T18:47:07.133196Z digest=sha256:5fda9c86f9d18252d956eae5f768a6591cf01445d1a2a026d0a4240f295cdfdd

Pith citing papers

No inbound Pith citation observations are available.