{"as_of":"2026-08-09T05:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:66d79e0754a6ccde79b705fd7025404482a9c55a933fb3ce5c8c8114a1b3c916","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:52:51.300393Z","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":"2026-08-04T21:25:28.137278Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2306.05500","last_updated":"2023-06-03T21:39:07Z","snapshot_observed_at":"2026-07-06T15:40:27.639368Z","submitted_at":"2023-06-03T21:39:07Z","title":"Word-Level Explanations for Analyzing Bias in Text-to-Image Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05500","snapshot_observed_at":"2026-08-07T13:52:51.300393Z","title":"M.; Tanneru, S","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20692","last_updated":"2025-05-27T04:01:03Z","snapshot_observed_at":"2026-08-08T12:07:29.911047Z","submitted_at":"2025-05-27T04:01:03Z","title":"Can we Debias Social Stereotypes in AI-Generated Images? Examining Text-to-Image Outputs and User Perceptions","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T13:52:51.300393Z"},"links":{"cited_paper":"/paper/2306.05500","citing_paper":"/paper/2505.20692"},"observation_digest":"sha256:405120407192533e43fbb4d5450a671ca79f59a707f577cea9c25443ec25bb44","observation_id":"35125cbd-eec4-49a7-bf3e-66472725cd23","resolution":{"observed_at":"2026-08-07T13:52:51.300393Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05500","last_updated":"2023-06-03T21:39:07Z","snapshot_observed_at":"2026-07-06T15:40:27.639368Z","submitted_at":"2023-06-03T21:39:07Z","title":"Word-Level Explanations for Analyzing Bias in Text-to-Image Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05500","snapshot_observed_at":"2026-08-05T05:01:36.805782Z","title":"Word-Level Explanations for Analyzing Bias in Text-to-Image Models.ArXiv, 2306.05500, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05786","last_updated":"2025-09-06T17:42:22Z","snapshot_observed_at":"2026-08-08T09:14:25.199933Z","submitted_at":"2025-09-06T17:42:22Z","title":"Effectively obtaining acoustic, visual and textual data from videos","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-05T05:01:36.805782Z"},"links":{"cited_paper":"/paper/2306.05500","citing_paper":"/paper/2509.05786"},"observation_digest":"sha256:4dd0039634eaaf56f5ba65349416362171e32a42cfc78cfadfcdf5e8d24106ee","observation_id":"02170d03-b9a9-48b0-9946-3de063dc4f0b","resolution":{"observed_at":"2026-08-05T05:01:36.805782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05500","last_updated":"2023-06-03T21:39:07Z","snapshot_observed_at":"2026-07-06T15:40:27.639368Z","submitted_at":"2023-06-03T21:39:07Z","title":"Word-Level Explanations for Analyzing Bias in Text-to-Image Models","version":1},"cited_work":{"arxiv_id":"2306.05500","doi":null,"metadata_source":"pith","pith_arxiv_id":"2306.05500","snapshot_observed_at":"2026-08-04T21:25:28.137278Z","title":"Word-Level Explanations for Analyzing Bias in Text-to-Image Models","venue":"cs.CL","work_id":"e99b6ebf-f2d9-4352-aa9f-dca0e5949c11","year":2023},"citing_paper":{"arxiv_id":"2509.09717","last_updated":"2025-09-09T18:57:10Z","snapshot_observed_at":"2026-08-08T11:56:25.298917Z","submitted_at":"2025-09-09T18:57:10Z","title":"Testing chatbots on the creation of encoders for audio conditioned image generation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-04T21:25:26.959197Z"},"links":{"cited_paper":"/paper/2306.05500","citing_paper":"/paper/2509.09717"},"observation_digest":"sha256:d416bad67c9834ce7da7f86f9fa1ca94b722ae33c5303decc0f802c5c3d49706","observation_id":"d24a96c5-b7d6-4c71-ab90-f8bde6247612","resolution":{"observed_at":"2026-08-04T21:25:28.146878Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2306.05500/citation-record","integrity":"/paper/2306.05500/integrity","json":"/paper/2306.05500/citation-record.json","paper":"/paper/2306.05500"},"outbound":[],"paper":{"arxiv_id":"2306.05500","last_updated":"2023-06-03T21:39:07Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T15:40:27.639368Z","submitted_at":"2023-06-03T21:39:07Z","title":"Word-Level Explanations for Analyzing Bias in Text-to-Image 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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.05500."}