{"as_of":"2026-08-23T01:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f3764d92de13f6df11256420ba403eee42e854bd3f6c438d6d97cf585c8d66ff","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:51:19.148997Z","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":"2026-05-16T23:58:42.780706Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-12T11:24:09.503294Z","title":"Face adapter for pre-trained diffusion models with fine-grained id and attribute control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18293","last_updated":"2024-12-10T11:13:57Z","snapshot_observed_at":"2026-08-17T22:47:03.630926Z","submitted_at":"2024-11-27T12:30:24Z","title":"HiFiVFS: High Fidelity Video Face Swapping","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T11:24:09.503294Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2411.18293"},"observation_digest":"sha256:7340b591abcd240d57347edae4f7bbfaf3aaf1d341dd5e8fa9ba058ffc015885","observation_id":"43654551-a261-410d-8a5d-9e29c0137519","resolution":{"observed_at":"2026-08-12T11:24:09.503294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-11T23:53:46.967995Z","title":"Face adapter for pre-trained diffusion models with fine-grained id and attribute control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02114","last_updated":"2025-03-18T10:51:59Z","snapshot_observed_at":"2026-08-20T06:05:03.037735Z","submitted_at":"2024-12-03T03:10:19Z","title":"Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T23:53:46.967995Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2412.02114"},"observation_digest":"sha256:f3d60b15ae7c32a317d72c2e43f9710f938b109c5b13b5e283302a7438d5d340","observation_id":"ff0e5600-1954-4947-b264-f1178ba81245","resolution":{"observed_at":"2026-08-11T23:53:46.967995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-11T05:23:02.013700Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17644","last_updated":"2025-01-18T11:08:25Z","snapshot_observed_at":"2026-08-18T11:03:05.231944Z","submitted_at":"2024-12-23T15:21:28Z","title":"DreamFit: Garment-Centric Human Generation via a Lightweight Anything-Dressing Encoder","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-11T05:23:02.013700Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2412.17644"},"observation_digest":"sha256:741ae1fea3f459db0c8cbd2eb1a77acf3d28571efe39aba4fce502fc972fa25e","observation_id":"6baca08b-2cf0-4607-b4a2-9194dfc2d329","resolution":{"observed_at":"2026-08-11T05:23:02.013700Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-11T00:10:16.491471Z","title":"Face adapter for pre-trained diffusion models with fine-grained id and attribute control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19645","last_updated":"2024-12-30T02:50:45Z","snapshot_observed_at":"2026-08-17T02:27:59.468242Z","submitted_at":"2024-12-27T13:49:25Z","title":"VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T00:10:16.491471Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2412.19645"},"observation_digest":"sha256:5c2d81c48fb2f35ebb0942fb15a5562a79f747c43bdd6e6863ada80aac6e2f63","observation_id":"36ad9b32-11f0-42c7-9b7b-271cd8988dde","resolution":{"observed_at":"2026-08-11T00:10:16.491471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-10T22:18:20.633052Z","title":"Face adapter for pre-trained diffusion models with fine- grained id and attribute control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.02064","last_updated":"2025-04-17T12:49:56Z","snapshot_observed_at":"2026-08-15T11:51:11.289466Z","submitted_at":"2025-01-03T19:17:27Z","title":"ArtCrafter: Text-Image Aligning Style Transfer via Embedding Reframing","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:18:20.633052Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2501.02064"},"observation_digest":"sha256:18c9bf6f61d988d9136f05ddb4572be6f238a7f92b3f72cb9a55dae2d987b53f","observation_id":"96613e86-ada4-49d7-bcad-112043893de5","resolution":{"observed_at":"2026-08-10T22:18:20.633052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-10T20:28:11.804923Z","title":"Face adapter for pre-trained diffusion models with fine-grained id and attribute control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.08553","last_updated":"2025-07-07T17:31:41Z","snapshot_observed_at":"2026-08-16T21:43:28.676337Z","submitted_at":"2025-01-15T03:28:14Z","title":"DynamicFace: High-Quality and Consistent Face Swapping for Image and Video using Composable 3D Facial Priors","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T20:28:11.804923Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2501.08553"},"observation_digest":"sha256:d0a0eb97d95b2f4a049e2e67c258fb849df6bcec453a475c5d7e6cf4a8b313bf","observation_id":"3f671d38-0690-4198-a865-632cc1879c48","resolution":{"observed_at":"2026-08-10T20:28:11.804923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-08-16T11:51:19.148997Z","title":"Face adapter for pre-trained diffusion models with fine-grained id and attribute control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.14509","last_updated":"2025-04-25T03:48:24Z","snapshot_observed_at":"2026-08-20T10:19:47.423559Z","submitted_at":"2025-04-20T06:53:00Z","title":"DreamID: High-Fidelity and Fast diffusion-based Face Swapping via Triplet ID Group Learning","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T11:51:19.148997Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2504.14509"},"observation_digest":"sha256:475214fbc8b514a4428834b2ec1453adb97aa31a11b73e3adf4c6330ce014490","observation_id":"0a529a44-68f5-4f75-95f3-08061dc4620d","resolution":{"observed_at":"2026-08-16T11:51:19.148997Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control","version":2},"cited_work":{"arxiv_id":"2405.12970","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.12970","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Face adapter for pre-trained diffusion models with fine-grained id and attribute control","venue":null,"work_id":"f2f2b669-1ae0-4403-8b1a-2108e6af1f5a","year":2024},"citing_paper":{"arxiv_id":"2512.07951","last_updated":"2026-04-03T06:55:22Z","snapshot_observed_at":"2026-08-11T13:56:05.871089Z","submitted_at":"2025-12-08T19:00:04Z","title":"Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-16T23:56:41.488788Z"},"links":{"cited_paper":"/paper/2405.12970","citing_paper":"/paper/2512.07951"},"observation_digest":"sha256:af839ed83ea8ae10966f42dcef0b3a3ca93db6bfe85691b47e8a90ab140c6bf1","observation_id":"6fa2c206-9bc8-47db-bf4b-a81537ac8d88","resolution":{"observed_at":"2026-05-16T23:58:42.783378Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.12970/citation-record","integrity":"/paper/2405.12970/integrity","json":"/paper/2405.12970/citation-record.json","paper":"/paper/2405.12970"},"outbound":[],"paper":{"arxiv_id":"2405.12970","last_updated":"2024-07-09T00:49:26Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-22T08:07:18.971323Z","submitted_at":"2024-05-21T17:50:12Z","title":"Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control"},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2405.12970."}