{"as_of":"2026-08-09T23:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0c4cef9c79a0d111a3bafb360b19fd2eb87b31d707ce26b5bd15e3d834234c79","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T18:47:07.133196Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2502.10266/citation-record","integrity":"/paper/2502.10266/integrity","json":"/paper/2502.10266/citation-record.json","paper":"/paper/2502.10266"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.084948Z","title":"Design and evaluation of crowdsourcing platforms based on users’ confidence judgments","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.084948Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:17ae03323e4b6c6c629d33e86c7c23075c40dd56b946aa27685f831cc7ceb555","observation_id":"b8bfb784-2b8c-49f1-b4c8-208003715bf7","resolution":{"observed_at":"2026-08-07T18:47:07.084948Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.093921Z","title":"The challenge of using LLMs to simulate human behavior: A causal inference perspective","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.093921Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:fdd9c605297dfc22f2441354de84562a70aed9c5a2302347fcfe2d81c9830411","observation_id":"b8b746e2-6b15-4844-b1a1-2b813d5f469f","resolution":{"observed_at":"2026-08-07T18:47:07.093921Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/icwsm.v18i1.31417","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.166632Z","title":"On the role of large language models in crowdsourcing misinformation assessment","venue":null,"work_id":"4e7fd3ae-54a5-41b9-ad43-a2bbf440e554","year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.129215Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:ba7de9c2e067b3885a4b205cc4687be06999b89ee64f23e92d9e287c8ad83e2c","observation_id":"04192d8f-6975-4641-ab55-890679b3b63f","resolution":{"observed_at":"2026-08-07T18:47:07.171802Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.16854","last_updated":"2024-04-05T15:19:19Z","snapshot_observed_at":"2026-08-08T23:14:03.294619Z","submitted_at":"2023-03-29T17:03:21Z","title":"AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.16854","snapshot_observed_at":"2026-08-07T18:47:07.097975Z","title":"Chatgpt in and for second language acquisition: A call for systematic research","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.097975Z"},"links":{"cited_paper":"/paper/2303.16854","citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:21ecf12cf8a244764f46470d90f2913f41d310ed109331f0dd3da6ff57370693","observation_id":"e0519ee4-f30a-4aa0-8d49-322c335e1070","resolution":{"observed_at":"2026-08-07T18:47:07.097975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11081","last_updated":"2025-01-24T08:44:20Z","snapshot_observed_at":"2026-08-07T21:22:02.895260Z","submitted_at":"2024-11-17T14:14:36Z","title":"The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11081","snapshot_observed_at":"2026-08-07T18:47:07.102184Z","title":"The promises and pitfalls of LLM annotations in dataset labeling: a case study on media bias detection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.102184Z"},"links":{"cited_paper":"/paper/2411.11081","citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:ff5738eb569e98f16467debba4c5ddbf479bd6bcfa41f8bba896fe2f7480a511","observation_id":"1df8bac3-7cfb-4be6-852d-24257bd48bd2","resolution":{"observed_at":"2026-08-07T18:47:07.102184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.118268Z","title":"ChatGPT vs","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.118268Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:92e13053091147ddb8a5d1e230082ec9b18dfd85eb44beaffb77cd6e410a3e6e","observation_id":"111734b8-9cad-48ca-a4e7-94b807c1066c","resolution":{"observed_at":"2026-08-07T18:47:07.118268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2410.23133","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.578202Z","title":"Crowdsourc- ing lexical diversity","venue":null,"work_id":"20fd0594-32d6-45ee-a627-40bcc9d5bd95","year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.111034Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:bbf8843d8bab2d9984a5bd34b4124f3e5a7b06e6013ea64505cda8a40ac8fb86","observation_id":"bf7a26aa-8ce5-4bb1-ae21-95903756f74b","resolution":{"observed_at":"2026-08-07T18:47:07.583374Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.114839Z","title":"ChatGPT: Jack of all trades, master of none","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.114839Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:a52f2defa0332923aedcb48268f20fa9260215b3e344038d14cfb96edbe8141c","observation_id":"64278b1a-3dce-4280-a938-eb667e882836","resolution":{"observed_at":"2026-08-07T18:47:07.114839Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.10808","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.368877Z","title":"Direct and indirect annotation with generative AI: A case study into finding animals and plants in historical text","venue":null,"work_id":"f93a0541-c9be-4cb4-8541-e0bae01841d1","year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.121572Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:a3615cf57d82ec42ad5bf94c8efd8c8a45bea5d210f05e1a2d41c5f36b1ba45c","observation_id":"e2298459-5aa5-45cc-a6d2-0587155b04be","resolution":{"observed_at":"2026-08-07T18:47:07.373657Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10168","last_updated":"2025-01-09T04:13:41Z","snapshot_observed_at":"2026-07-06T15:55:59.949673Z","submitted_at":"2023-07-19T17:54:43Z","title":"LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10168","snapshot_observed_at":"2026-08-07T18:47:07.125085Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.125085Z"},"links":{"cited_paper":"/paper/2307.10168","citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:73c7f67b177c1d74aa89cb2ff9cb98b1a62f39cec1b3acfcf8f143ac5cbb33cc","observation_id":"d89d0167-ab84-4944-822d-e4a461a9660d","resolution":{"observed_at":"2026-08-07T18:47:07.125085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.21958","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.685212Z","title":"doi:10.1017/pan.2023.2","venue":null,"work_id":"8b1f218d-5ec2-4ec7-b330-3571c8c3909a","year":2023},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.089185Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:9885f8455e021f8a31ef9782184fb4a4344d509c35d623e4c820d4805a75bdfa","observation_id":"b64532d1-aad2-43ea-9b5a-c21d8987fa30","resolution":{"observed_at":"2026-08-07T18:47:07.690514Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.14379","last_updated":"2024-10-20T12:00:19Z","snapshot_observed_at":"2026-07-06T16:23:30.533693Z","submitted_at":"2023-09-24T14:21:50Z","title":"Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.14379","snapshot_observed_at":"2026-08-07T18:47:07.106548Z","title":"Andres Karjus and Christine Cuskley","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.106548Z"},"links":{"cited_paper":"/paper/2309.14379","citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:0d210e9eed5ba641ceb53861f98b61ea596f9cded151b03e5427a1eb8d8d62f6","observation_id":"1d51aa29-d65f-4b58-879f-aceb71a39baf","resolution":{"observed_at":"2026-08-07T18:47:07.106548Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T18:47:07.133196Z","title":"URL https://direct.mit.edu/coli/article/50/1/237/118498/ Can-Large-Language-Models-Transform-Computational","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?","version":1},"reference_index":9312,"source":"pdf_text","source_observed_at":"2026-08-07T18:47:07.133196Z"},"links":{"citing_paper":"/paper/2502.10266"},"observation_digest":"sha256:5fda9c86f9d18252d956eae5f768a6591cf01445d1a2a026d0a4240f295cdfdd","observation_id":"92c0cf15-3300-4fe1-88c6-f4c439b63762","resolution":{"observed_at":"2026-08-07T18:47:07.133196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.10266","last_updated":"2025-02-14T16:23:39Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T18:40:49.690750Z","submitted_at":"2025-02-14T16:23:39Z","title":"Are Large Language Models the future crowd workers of Linguistics?"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":8,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":13},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"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."}