{"as_of":"2026-08-08T01:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:02868cab8db52fea6ca65e4b9ba95805e97352ef13e4dcc304dc7603ff45c8ab","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:03:11.133006Z","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":"2026-07-04T16:29:57.666142Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-08-07T11:03:11.133006Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03660","last_updated":"2025-06-30T13:33:45Z","snapshot_observed_at":"2026-08-07T10:55:36.329837Z","submitted_at":"2025-06-04T07:49:11Z","title":"INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T11:03:11.133006Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2506.03660"},"observation_digest":"sha256:e596a34209e64ba15aa64232e29de11875aea9ab7b0510dd99a500e80ea95346","observation_id":"b603acf4-372f-47b6-b1d2-2f4549077463","resolution":{"observed_at":"2026-08-07T11:03:11.133006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-08-06T17:27:17.568476Z","title":"Exploring plain vit reconstruction for multi- class unsupervised anomaly detection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.11003","last_updated":"2025-07-15T05:42:17Z","snapshot_observed_at":"2026-08-06T17:16:42.077432Z","submitted_at":"2025-07-15T05:42:17Z","title":"Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T17:27:17.568476Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2507.11003"},"observation_digest":"sha256:374cf236291dda2136c3f838346cd2b5734c39ebe2a5df8f5111aba7a8bb9485","observation_id":"655acc46-4bff-427d-8d08-9904aa7be194","resolution":{"observed_at":"2026-08-06T17:27:17.568476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2312.07495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-07-04T16:29:57.666142Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","venue":null,"work_id":"20fae842-4048-4fc4-8b38-98aeec0b23f1","year":2023},"citing_paper":{"arxiv_id":"2604.08301","last_updated":"2026-04-09T14:34:50Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:34:50Z","title":"GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-10T18:27:36.529298Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2604.08301"},"observation_digest":"sha256:d08e4bc93182bda49ac42a35acbf75b8835ee2ce54487b88bf48e439ba091789","observation_id":"dca69b14-7792-44bc-a141-4effbd691fb5","resolution":{"observed_at":"2026-05-11T00:30:55.453990Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2312.07495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-07-04T16:29:57.666142Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","venue":null,"work_id":"20fae842-4048-4fc4-8b38-98aeec0b23f1","year":2023},"citing_paper":{"arxiv_id":"2605.08664","last_updated":"2026-05-09T04:04:41Z","snapshot_observed_at":"2026-07-06T23:20:52.521341Z","submitted_at":"2026-05-09T04:04:41Z","title":"IPAD-CLIP: Teaching CLIP to Detect Image Local Perceptual Artifacts","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-12T01:29:17.126354Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2605.08664"},"observation_digest":"sha256:c726ee5a3cb5f51c5821a169a12c6316e4fd321ad373ca236877c1a07a0bac6e","observation_id":"aba7357b-ee14-4e52-b7f7-c976bb814b37","resolution":{"observed_at":"2026-05-12T07:56:28.079347Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2312.07495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-07-04T16:29:57.666142Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","venue":null,"work_id":"20fae842-4048-4fc4-8b38-98aeec0b23f1","year":2023},"citing_paper":{"arxiv_id":"2605.24402","last_updated":"2026-05-23T05:10:18Z","snapshot_observed_at":"2026-07-06T23:34:28.608412Z","submitted_at":"2026-05-23T05:10:18Z","title":"Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-30T13:48:39.954133Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2605.24402"},"observation_digest":"sha256:fca058459bb4f80651342bee175b84522366ad12d3fa3b69466ae5b5860744ee","observation_id":"84fc82d1-7270-4780-bfb0-58548442928c","resolution":{"observed_at":"2026-06-30T13:54:44.015384Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2312.07495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-07-04T16:29:57.666142Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","venue":null,"work_id":"20fae842-4048-4fc4-8b38-98aeec0b23f1","year":2023},"citing_paper":{"arxiv_id":"2606.23126","last_updated":"2026-06-22T10:14:06Z","snapshot_observed_at":"2026-08-06T04:53:15.870807Z","submitted_at":"2026-06-22T10:14:06Z","title":"MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-26T09:26:51.456652Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2606.23126"},"observation_digest":"sha256:3c7203310eab71447e0ba66662b58681ad8b9c7558bf12d0454f32afca5dc1a1","observation_id":"7253b312-e647-444b-bced-12982a8db51a","resolution":{"observed_at":"2026-07-04T09:49:44.633986Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2312.07495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-07-04T16:29:57.666142Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","venue":null,"work_id":"20fae842-4048-4fc4-8b38-98aeec0b23f1","year":2023},"citing_paper":{"arxiv_id":"2606.24375","last_updated":"2026-06-23T10:07:54Z","snapshot_observed_at":"2026-08-04T15:26:53.242353Z","submitted_at":"2026-06-23T10:07:54Z","title":"MATCH: Flow Matching for Multi-View Anomaly Detection","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-06-26T00:32:33.173587Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2606.24375"},"observation_digest":"sha256:d558ef882bdb4fe53c1fdcb859617d37d86f0066a96bbdc2a29c0d5ac75856e1","observation_id":"328edd2e-e0d8-4434-8151-db12dc8ac2ef","resolution":{"observed_at":"2026-07-04T16:29:57.667655Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":"2312.07495","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-07-04T16:29:57.666142Z","title":"Exploring plain vit reconstruction for multi-class unsupervised anomaly detection","venue":null,"work_id":"20fae842-4048-4fc4-8b38-98aeec0b23f1","year":2023},"citing_paper":{"arxiv_id":"2607.02252","last_updated":"2026-08-02T02:52:11Z","snapshot_observed_at":"2026-08-06T23:24:46.709910Z","submitted_at":"2026-07-02T14:43:21Z","title":"ArcAD: Anomaly-Rectified Calibration for Cold-Start Supervised Anomaly Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-03T15:49:13.410168Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2607.02252"},"observation_digest":"sha256:f91eebc3372200b147fc8a5bcd11cfca5577ed9f42037a3ff6b42c27e718225a","observation_id":"20865458-dd3d-436f-b46c-35d8f8c9cd69","resolution":{"observed_at":"2026-07-03T15:58:37.599170Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-08-04T04:36:17.266927Z","title":"arXiv preprint arXiv:2312.07495 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02252","last_updated":"2026-08-02T02:52:11Z","snapshot_observed_at":"2026-08-06T23:24:46.709910Z","submitted_at":"2026-07-02T14:43:21Z","title":"ArcAD: Anomaly-Rectified Calibration for Cold-Start Supervised Anomaly Detection","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-04T04:36:17.266927Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2607.02252"},"observation_digest":"sha256:d3cba3ded6221d911b0762c4dc40e59767118f9253686d8823311e91e1bc571c","observation_id":"0f9e1a30-ec33-435a-b082-a1253dbd31ed","resolution":{"observed_at":"2026-08-04T04:36:17.266927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-08-01T13:42:17.774748Z","title":"arXiv preprint arXiv:2312.07495 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19032","last_updated":"2026-07-21T12:19:33Z","snapshot_observed_at":"2026-08-01T13:42:11.454760Z","submitted_at":"2026-07-21T12:19:33Z","title":"IMMoE: Incomplete Multi-View Anomaly Detection via Mixture of View Experts Fusion","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-01T13:42:17.774748Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2607.19032"},"observation_digest":"sha256:012fb0d376ea5d013947a9dcf64e49a2b68defaf7eca47eaa7fb6db7e6e5d41c","observation_id":"9115776b-f645-4086-b726-b44f73a09827","resolution":{"observed_at":"2026-08-01T13:42:17.774748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07495","snapshot_observed_at":"2026-08-04T20:50:20.805168Z","title":"arXiv preprint arXiv:2312.07495 (2023) 21","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.01793","last_updated":"2026-08-03T07:03:51Z","snapshot_observed_at":"2026-08-06T23:33:02.918333Z","submitted_at":"2026-08-03T07:03:51Z","title":"ReFP-AD: Rectified Flow Preconditioning for Energy-Based Anomaly Detection","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-04T20:50:20.805168Z"},"links":{"cited_paper":"/paper/2312.07495","citing_paper":"/paper/2608.01793"},"observation_digest":"sha256:a2a573e1b559d3df30f9558d5108afb1ca1e183a0f27edd312e5ccc8e0064e54","observation_id":"14a3e953-79f4-4bdc-90f3-ec0c110b6589","resolution":{"observed_at":"2026-08-04T20:50:20.805168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2312.07495/citation-record","integrity":"/paper/2312.07495/integrity","json":"/paper/2312.07495/citation-record.json","paper":"/paper/2312.07495"},"outbound":[],"paper":{"arxiv_id":"2312.07495","last_updated":"2024-08-11T14:27:16Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T17:00:37.507046Z","submitted_at":"2023-12-12T18:28:59Z","title":"Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2312.07495."}