{"as_of":"2026-08-09T21:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b049ad4b1f1b806ab350a73fd114625a4e168d2d7bc0e0b1e5ac8c0c333a9ff8","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:14:47.415735Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T16:32:11.100955Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.04186","last_updated":"2022-10-11T01:31:37Z","snapshot_observed_at":"2026-08-09T19:13:45.060896Z","submitted_at":"2022-10-09T06:35:14Z","title":"Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.04186","snapshot_observed_at":"2026-08-06T20:14:47.415735Z","title":"Accessed: 19/02/2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.03405","last_updated":"2025-07-04T09:13:50Z","snapshot_observed_at":"2026-08-09T19:12:28.054035Z","submitted_at":"2025-07-04T09:13:50Z","title":"Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T20:14:47.415735Z"},"links":{"cited_paper":"/paper/2210.04186","citing_paper":"/paper/2507.03405"},"observation_digest":"sha256:2a678d2aeccf9f0a60afcba9efd6ed4bf3584f1f429e0f59cfd85609bfac653b","observation_id":"b62697b1-d33d-43b7-af01-8d749ce58ed1","resolution":{"observed_at":"2026-08-06T20:14:47.415735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.04186","last_updated":"2022-10-11T01:31:37Z","snapshot_observed_at":"2026-08-09T19:13:45.060896Z","submitted_at":"2022-10-09T06:35:14Z","title":"Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT","version":2},"cited_work":{"arxiv_id":"2210.04186","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.04186","snapshot_observed_at":"2026-08-06T16:32:11.100955Z","title":"Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT","venue":"cs.CL","work_id":"c7bbde40-30f9-4eeb-8555-eacacce12fb5","year":2022},"citing_paper":{"arxiv_id":"2507.13238","last_updated":"2025-07-23T21:50:22Z","snapshot_observed_at":"2026-08-09T19:14:00.468685Z","submitted_at":"2025-07-17T15:47:49Z","title":"Multilingual LLMs Are Not Multilingual Thinkers: Evidence from Hindi Analogy Evaluation","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T16:32:09.683112Z"},"links":{"cited_paper":"/paper/2210.04186","citing_paper":"/paper/2507.13238"},"observation_digest":"sha256:90dbabcb3183ec4c4d5d509a9a66202108412fa961bc6f0901e56edad5026a77","observation_id":"7b511a61-1524-4af1-a793-c75c6e00a826","resolution":{"observed_at":"2026-08-06T16:32:11.166094Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2210.04186/citation-record","integrity":"/paper/2210.04186/integrity","json":"/paper/2210.04186/citation-record.json","paper":"/paper/2210.04186"},"outbound":[],"paper":{"arxiv_id":"2210.04186","last_updated":"2022-10-11T01:31:37Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T19:13:45.060896Z","submitted_at":"2022-10-09T06:35:14Z","title":"Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT"},"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":"2026-08-09T06:31:02.800959+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 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.04186."}