{"as_of":"2026-08-10T06:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:af224714b197c44a9bab2156398b3511bded7c3d71e51759c1ce05abf8d7b0cd","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":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:57:49.134717Z","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":"2026-07-10T03:36:44.076584Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2411.15633","last_updated":"2025-05-20T12:06:56Z","snapshot_observed_at":"2026-08-06T14:53:33.853203Z","submitted_at":"2024-11-23T19:10:32Z","title":"Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection","version":4},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-05-17T23:25:47.549655Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2411.15633"},"observation_digest":"sha256:db5fde67b079b1663c2171d8ca2183908782ad57133b720d2ff9ce2fcbaa8966","observation_id":"d8d98dd6-6ce7-4824-9a44-f62d256b02bf","resolution":{"observed_at":"2026-05-17T23:25:47.769354Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-08-06T14:57:49.134717Z","title":"Detecting GAN generated fake images using co-occurrence matrices","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"2507.17240","last_updated":"2025-07-23T06:18:09Z","snapshot_observed_at":"2026-08-10T00:44:41.983347Z","submitted_at":"2025-07-23T06:18:09Z","title":"Perceptual Classifiers: Detecting Generative Images using Perceptual Features","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T14:57:49.134717Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2507.17240"},"observation_digest":"sha256:7e046be3cbfb16e38d9d9b523a0d26dbb08478b872dc79379f1fb1772e33fc35","observation_id":"cb641314-bfaf-46ba-8c29-42ff35b03793","resolution":{"observed_at":"2026-08-06T14:57:49.134717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-08-06T01:04:10.675782Z","title":"Detecting gan generated fake images using co-occurrence matrices","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"2508.03967","last_updated":"2025-08-05T23:10:56Z","snapshot_observed_at":"2026-08-09T11:30:50.841071Z","submitted_at":"2025-08-05T23:10:56Z","title":"RAVID: Retrieval-Augmented Visual Detection: A Knowledge-Driven Approach for AI-Generated Image Identification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T01:04:10.675782Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2508.03967"},"observation_digest":"sha256:1c542e09b5f260bed9d25bbf25f4e39ec23c1cac6b5c590b9eeadd3f050f15d1","observation_id":"2d344a66-5f6a-4384-9c62-205772ddd8e7","resolution":{"observed_at":"2026-08-06T01:04:10.675782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2604.03833","last_updated":"2026-04-04T19:19:33Z","snapshot_observed_at":"2026-07-31T21:57:51.775373Z","submitted_at":"2026-04-04T19:19:33Z","title":"SPARK-IL: Spectral Retrieval-Augmented RAG for Knowledge-driven Deepfake Detection via Incremental Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-13T17:02:08.798342Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2604.03833"},"observation_digest":"sha256:ef475944fbe3d5fae1274464e7226afc75373fbe6b9d2ee07462dc874c0b10a9","observation_id":"8e40db89-d45c-4456-be64-e920ff9b5885","resolution":{"observed_at":"2026-05-13T17:03:01.242048Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2604.04608","last_updated":"2026-04-06T11:50:29Z","snapshot_observed_at":"2026-08-06T06:14:55.966523Z","submitted_at":"2026-04-06T11:50:29Z","title":"Beyond Semantics: Uncovering the Physics of Fakes via Universal Physical Descriptors for Cross-Modal Synthetic Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T18:52:34.752473Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2604.04608"},"observation_digest":"sha256:976c14e8a1c72461cd130391fcd7b3413a662ea7914be1600854bd6db5c6aaa0","observation_id":"76aeb8a7-47f9-4fed-8bc1-159c205cbbf2","resolution":{"observed_at":"2026-05-10T23:45:53.228729Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2604.14570","last_updated":"2026-04-16T03:02:04Z","snapshot_observed_at":"2026-07-06T23:02:18.425249Z","submitted_at":"2026-04-16T03:02:04Z","title":"Deepfake Detection Generalization with Diffusion Noise","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-10T11:22:31.988852Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2604.14570"},"observation_digest":"sha256:d4e6da04951f4943c7100bf0172e80281df37a9c5cf895a576acd90a92dcb0c3","observation_id":"1c851c53-c984-401a-b2dd-901d2e38d452","resolution":{"observed_at":"2026-05-10T11:25:19.560586Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2604.16987","last_updated":"2026-08-06T06:53:47Z","snapshot_observed_at":"2026-08-09T23:09:40.169997Z","submitted_at":"2026-04-18T13:22:42Z","title":"DVAR: Adversarial Multi-Agent Debate for Video Authenticity Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T07:51:04.580617Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2604.16987"},"observation_digest":"sha256:edba769d55eab99088a0ea0ca944a8abe74cb8227ec164a2f77761f0cbcc64f4","observation_id":"7c7a35ff-a3e4-4305-801d-551c1ca523fe","resolution":{"observed_at":"2026-05-10T07:52:13.681480Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2605.14799","last_updated":"2026-05-26T08:32:11Z","snapshot_observed_at":"2026-07-06T23:26:13.644646Z","submitted_at":"2026-05-14T13:09:16Z","title":"Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-30T21:17:16.489486Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2605.14799"},"observation_digest":"sha256:f0daac91d65d30509a8f22569f9e280c82f88d5322d8a7f7d163628fe4603ac3","observation_id":"b0b091a7-758b-4e40-9860-61b2d101be3b","resolution":{"observed_at":"2026-07-01T14:25:47.216331Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":"1903.06836","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-07-10T03:36:44.076584Z","title":"M., Chandrasekaran, S., Flenner, A., Bappy, J","venue":"cs.CV","work_id":"513fa971-7c89-4ab2-ade8-9b5c9bdb0894","year":2019},"citing_paper":{"arxiv_id":"2607.08674","last_updated":"2026-07-09T16:36:54Z","snapshot_observed_at":"2026-08-07T13:18:23.735745Z","submitted_at":"2026-07-09T16:36:54Z","title":"Do Transformations Reveal the Truth? Generative Residual Learning for Generalized AI-Generated Image Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-10T03:28:57.522947Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2607.08674"},"observation_digest":"sha256:8029420bb02dc58f85a64e3744066f428fa852c241112c09587de0a124a89bc0","observation_id":"65c67fb0-513c-4e39-8a62-55e071181991","resolution":{"observed_at":"2026-07-10T03:36:44.078800Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-08-01T15:27:44.937065Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20564","last_updated":"2026-08-04T02:51:42Z","snapshot_observed_at":"2026-08-08T23:19:51.370003Z","submitted_at":"2026-07-20T19:05:20Z","title":"PhantomSeal: Proactive Deepfakes Defense with Identity/Context Protection and Forensic Tracing","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-01T15:27:44.937065Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2607.20564"},"observation_digest":"sha256:e485551cd6c2c9d7713b791d3dbb13d989d92d0dadb4dc438ae0684989aeffed","observation_id":"6b91d19d-8117-4a1f-83fd-337017ffe0e1","resolution":{"observed_at":"2026-08-01T15:27:44.937065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-08-01T01:04:33.824531Z","title":"https://doi.org/10.48550/arXiv.1903.06836","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"2607.25962","last_updated":"2026-07-28T16:45:52Z","snapshot_observed_at":"2026-08-06T09:14:07.805736Z","submitted_at":"2026-07-28T16:45:52Z","title":"LaP-Forensics: Latent-Pixel Consistency Guided Multimodal Reasoning for Deepfake Detection","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-01T01:04:33.824531Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2607.25962"},"observation_digest":"sha256:ace0b9777a3de1ed04b4843c9fab28aab7cd2de63255e3015f47e98ece8aedcc","observation_id":"bdcb6bc1-5771-4b90-a41a-64277623a1f8","resolution":{"observed_at":"2026-08-01T01:04:33.824531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.06836","snapshot_observed_at":"2026-08-05T00:46:23.224321Z","title":"arXiv preprint arXiv:1903.06836 , year=","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"2608.00559","last_updated":"2026-08-01T09:42:45Z","snapshot_observed_at":"2026-08-08T15:42:31.128764Z","submitted_at":"2026-08-01T09:42:45Z","title":"Test-Time Curriculum for Open-Set AIGC Detection","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-05T00:46:23.224321Z"},"links":{"cited_paper":"/paper/1903.06836","citing_paper":"/paper/2608.00559"},"observation_digest":"sha256:31be69ea5f9e995eb2f36a041c94a718513cb55aefb3626f12ad03039a67039e","observation_id":"71ef5b97-3406-4a87-a851-e78e71aadd27","resolution":{"observed_at":"2026-08-05T00:46:23.224321Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1903.06836/citation-record","integrity":"/paper/1903.06836/integrity","json":"/paper/1903.06836/citation-record.json","paper":"/paper/1903.06836"},"outbound":[],"paper":{"arxiv_id":"1903.06836","last_updated":"2019-10-03T00:54:21Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-01T12:10:45.739753Z","submitted_at":"2019-03-15T23:24:08Z","title":"Detecting GAN generated Fake Images using Co-occurrence Matrices"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:1903.06836."}