{"as_of":"2026-08-10T03:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:26cd09078c744c101bc3e2b3ca9841a6da14eaca033c0a63ff24aa737d1fef25","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":"2026-06-30T01:08:22.794058Z","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":"2026-07-01T15:45:48.486161Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2304.06408","last_updated":"2023-06-29T15:33:42Z","snapshot_observed_at":"2026-08-10T00:00:45.591987Z","submitted_at":"2023-04-13T11:13:19Z","title":"Intriguing properties of synthetic images: from generative adversarial networks to diffusion models","version":2},"cited_work":{"arxiv_id":"2304.06408","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06408","snapshot_observed_at":"2026-07-01T15:45:48.486161Z","title":"arXiv:2304.06408","venue":null,"work_id":"5aea0932-ec48-4e9c-9d40-bacd16c3c4b2","year":2023},"citing_paper":{"arxiv_id":"2507.10236","last_updated":"2026-05-15T17:35:28Z","snapshot_observed_at":"2026-07-06T21:56:49.263374Z","submitted_at":"2025-07-14T12:56:55Z","title":"Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters?","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-21T23:31:40.691896Z"},"links":{"cited_paper":"/paper/2304.06408","citing_paper":"/paper/2507.10236"},"observation_digest":"sha256:6317ca2f0c6bb2f8ed9816de43ed9a636d15d760f3297272c81f286bb54cd130","observation_id":"58b05fa2-77c8-471b-8ce9-8cd369058e7f","resolution":{"observed_at":"2026-05-21T23:34:26.611487Z","resolver_source":"arxiv_id","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":"2304.06408","last_updated":"2023-06-29T15:33:42Z","snapshot_observed_at":"2026-08-10T00:00:45.591987Z","submitted_at":"2023-04-13T11:13:19Z","title":"Intriguing properties of synthetic images: from generative adversarial networks to diffusion models","version":2},"cited_work":{"arxiv_id":"2304.06408","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06408","snapshot_observed_at":"2026-07-01T15:45:48.486161Z","title":"arXiv:2304.06408","venue":null,"work_id":"5aea0932-ec48-4e9c-9d40-bacd16c3c4b2","year":2023},"citing_paper":{"arxiv_id":"2606.28510","last_updated":"2026-06-26T18:05:08Z","snapshot_observed_at":"2026-08-07T22:06:21.947417Z","submitted_at":"2026-06-26T18:05:08Z","title":"Generative AI Literacy Training Improves Intelligence Analysts' Discrimination of Real and AI-Generated Images","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T01:08:22.794058Z"},"links":{"cited_paper":"/paper/2304.06408","citing_paper":"/paper/2606.28510"},"observation_digest":"sha256:807ca6320f7fe35199f0e30ad1cafbaa5c085e3e6d82343862f3cd552b5ba0a1","observation_id":"86a1e2f6-0238-432c-966d-6df55d211fa7","resolution":{"observed_at":"2026-07-01T15:45:48.487556Z","resolver_source":"arxiv_id","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"}}],"links":{"evidence":"/evidence","html":"/paper/2304.06408/citation-record","integrity":"/paper/2304.06408/integrity","json":"/paper/2304.06408/citation-record.json","paper":"/paper/2304.06408"},"outbound":[],"paper":{"arxiv_id":"2304.06408","last_updated":"2023-06-29T15:33:42Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T00:00:45.591987Z","submitted_at":"2023-04-13T11:13:19Z","title":"Intriguing properties of synthetic images: from generative adversarial networks to diffusion models"},"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 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.06408."}