{"as_of":"2026-08-07T23:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e2e71cdce4a9934e0762b9d450767bae41486cd67fc41e987318df07a5e8c34b","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:19:30.128678Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-17T08:39:28.164364Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.02179","last_updated":"2024-05-29T12:29:08Z","snapshot_observed_at":"2026-08-03T02:07:54.986202Z","submitted_at":"2023-07-05T10:15:07Z","title":"Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning","version":2},"cited_work":{"arxiv_id":"2307.02179","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.02179","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Open-Source Large Language Models Out- perform Crowd Workers and Approach ChatGPT in Text- Annotation Tasks","venue":null,"work_id":"f179cce8-dc46-44e8-bc76-ac9fbfb95bad","year":2023},"citing_paper":{"arxiv_id":"2308.03825","last_updated":"2024-05-15T12:06:31Z","snapshot_observed_at":"2026-07-06T16:03:34.432602Z","submitted_at":"2023-08-07T16:55:20Z","title":"\"Do Anything Now\": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-17T08:39:28.047394Z"},"links":{"cited_paper":"/paper/2307.02179","citing_paper":"/paper/2308.03825"},"observation_digest":"sha256:527b4ca8121756abcca2dfb1cb2fe0420c9685217b74c3c9152d0d6e98c356b7","observation_id":"8d9c085d-6e39-4ae5-8ef4-c2bd198a7064","resolution":{"observed_at":"2026-05-17T08:39:28.167017Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02179","last_updated":"2024-05-29T12:29:08Z","snapshot_observed_at":"2026-08-03T02:07:54.986202Z","submitted_at":"2023-07-05T10:15:07Z","title":"Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02179","snapshot_observed_at":"2026-08-06T21:19:30.128678Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.00543","last_updated":"2025-07-01T08:04:58Z","snapshot_observed_at":"2026-08-06T21:10:16.441448Z","submitted_at":"2025-07-01T08:04:58Z","title":"Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T21:19:30.128678Z"},"links":{"cited_paper":"/paper/2307.02179","citing_paper":"/paper/2507.00543"},"observation_digest":"sha256:9c0f936bd78de7aaf0552ca89df5aaecfbc9708f4efddeca7fd83596dac46495","observation_id":"e3bfb64a-b552-4833-937c-372c05629403","resolution":{"observed_at":"2026-08-06T21:19:30.128678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02179","last_updated":"2024-05-29T12:29:08Z","snapshot_observed_at":"2026-08-03T02:07:54.986202Z","submitted_at":"2023-07-05T10:15:07Z","title":"Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02179","snapshot_observed_at":"2026-08-05T21:53:04.125439Z","title":"Open-source large language models out- perform crowd workers and approach chatgpt in text-annotation tasks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.07819","last_updated":"2026-03-27T07:03:50Z","snapshot_observed_at":"2026-08-07T20:45:07.541937Z","submitted_at":"2025-08-11T10:03:45Z","title":"ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection","version":6},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-05T21:53:04.125439Z"},"links":{"cited_paper":"/paper/2307.02179","citing_paper":"/paper/2508.07819"},"observation_digest":"sha256:bf4106a95b3e2a4485ca29937ec13ed9e1ca6b22d3f8a068b087b9b9ee04e8ba","observation_id":"db92829f-04e8-4e15-9388-a6100d99a3d8","resolution":{"observed_at":"2026-08-05T21:53:04.125439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02179","last_updated":"2024-05-29T12:29:08Z","snapshot_observed_at":"2026-08-03T02:07:54.986202Z","submitted_at":"2023-07-05T10:15:07Z","title":"Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02179","snapshot_observed_at":"2026-08-05T21:57:58.829185Z","title":"Open-source large language models outperform crowd workers and approach chatgpt in text-annotation tasks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.07827","last_updated":"2025-08-11T10:19:10Z","snapshot_observed_at":"2026-08-07T20:45:29.055602Z","submitted_at":"2025-08-11T10:19:10Z","title":"Evaluating Large Language Models as Expert Annotators","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-05T21:57:58.829185Z"},"links":{"cited_paper":"/paper/2307.02179","citing_paper":"/paper/2508.07827"},"observation_digest":"sha256:326c567536261894ab046e9e58fbe17925b0f30d57ec2faeec7a2009b1bf953e","observation_id":"1d58986c-7e14-4e38-8c82-ee71a1672364","resolution":{"observed_at":"2026-08-05T21:57:58.829185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2307.02179/citation-record","integrity":"/paper/2307.02179/integrity","json":"/paper/2307.02179/citation-record.json","paper":"/paper/2307.02179"},"outbound":[],"paper":{"arxiv_id":"2307.02179","last_updated":"2024-05-29T12:29:08Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-03T02:07:54.986202Z","submitted_at":"2023-07-05T10:15:07Z","title":"Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2307.02179."}