{"as_of":"2026-08-17T21:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:013926e20b1592723c713b03ef7a3a9cc42af8ce94d7b6f0e37a70717ea060aa","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T05:44:15.718289Z","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":"2026-05-14T02:10:27.591382Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.09785","last_updated":"2022-07-06T18:56:54Z","snapshot_observed_at":"2026-08-17T15:24:23.046977Z","submitted_at":"2021-06-17T19:57:33Z","title":"Efficient Self-supervised Vision Transformers for Representation Learning","version":2},"cited_work":{"arxiv_id":"2106.09785","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.09785","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficient self-supervised vision transformers for representation learning","venue":null,"work_id":"e1917362-f7ab-4e00-8f21-57a21257f2d9","year":null},"citing_paper":{"arxiv_id":"2111.07832","last_updated":"2022-01-27T09:20:49Z","snapshot_observed_at":"2026-07-06T12:08:39.149450Z","submitted_at":"2021-11-15T15:18:05Z","title":"iBOT: Image BERT Pre-Training with Online Tokenizer","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-14T02:10:27.569787Z"},"links":{"cited_paper":"/paper/2106.09785","citing_paper":"/paper/2111.07832"},"observation_digest":"sha256:f606cc981097b20b5d5af4f5f285e97ac0e990a3f9c3a4d6c9fe5f3b6af7510d","observation_id":"a20ae6eb-c455-4ef2-bc08-fd1e244be254","resolution":{"observed_at":"2026-05-14T02:10:27.595160Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09785","last_updated":"2022-07-06T18:56:54Z","snapshot_observed_at":"2026-08-17T15:24:23.046977Z","submitted_at":"2021-06-17T19:57:33Z","title":"Efficient Self-supervised Vision Transformers for Representation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09785","snapshot_observed_at":"2026-08-12T14:44:17.127222Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.14953","last_updated":"2024-11-22T14:12:35Z","snapshot_observed_at":"2026-08-16T20:09:49.701345Z","submitted_at":"2024-11-22T14:12:35Z","title":"Evaluating Vision Transformer Models for Visual Quality Control in Industrial Manufacturing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T14:44:17.127222Z"},"links":{"cited_paper":"/paper/2106.09785","citing_paper":"/paper/2411.14953"},"observation_digest":"sha256:bdc30078679587411dd44078126e241b00a058fa75c7d334407d79c3055513c7","observation_id":"0a770448-b49f-4d77-a908-8c8e8a140dea","resolution":{"observed_at":"2026-08-12T14:44:17.127222Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09785","last_updated":"2022-07-06T18:56:54Z","snapshot_observed_at":"2026-08-17T15:24:23.046977Z","submitted_at":"2021-06-17T19:57:33Z","title":"Efficient Self-supervised Vision Transformers for Representation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09785","snapshot_observed_at":"2026-08-16T05:44:15.718289Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.19888","last_updated":"2025-04-28T15:23:28Z","snapshot_observed_at":"2026-08-16T14:45:21.022251Z","submitted_at":"2025-04-28T15:23:28Z","title":"Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-16T05:44:15.718289Z"},"links":{"cited_paper":"/paper/2106.09785","citing_paper":"/paper/2504.19888"},"observation_digest":"sha256:b7c9a141e2e13330c2d400e9d2aacec7acc2aefddebe46aa6af958154b082387","observation_id":"d7ae4e06-d3ee-4f6c-a930-2450346d26a0","resolution":{"observed_at":"2026-08-16T05:44:15.718289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09785","last_updated":"2022-07-06T18:56:54Z","snapshot_observed_at":"2026-08-17T15:24:23.046977Z","submitted_at":"2021-06-17T19:57:33Z","title":"Efficient Self-supervised Vision Transformers for Representation Learning","version":2},"cited_work":{"arxiv_id":"2106.09785","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.09785","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficient self-supervised vision transformers for representation learning","venue":null,"work_id":"e1917362-f7ab-4e00-8f21-57a21257f2d9","year":null},"citing_paper":{"arxiv_id":"2605.11870","last_updated":"2026-05-12T09:50:11Z","snapshot_observed_at":"2026-08-13T09:09:41.689237Z","submitted_at":"2026-05-12T09:50:11Z","title":"Information theoretic underpinning of self-supervised learning by clustering","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-05-13T06:22:03.439595Z"},"links":{"cited_paper":"/paper/2106.09785","citing_paper":"/paper/2605.11870"},"observation_digest":"sha256:75f135cdd8103a18d9c95a2e245e2ca568aa1849e02dbb624592ed5138458a5e","observation_id":"23afbe91-3470-4ed9-9088-096b90a142d9","resolution":{"observed_at":"2026-05-13T06:22:23.147515Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09785","last_updated":"2022-07-06T18:56:54Z","snapshot_observed_at":"2026-08-17T15:24:23.046977Z","submitted_at":"2021-06-17T19:57:33Z","title":"Efficient Self-supervised Vision Transformers for Representation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09785","snapshot_observed_at":"2026-08-16T00:22:07.624836Z","title":"Efficient","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.12084","last_updated":"2026-08-12T14:07:09Z","snapshot_observed_at":"2026-08-16T00:50:45.268717Z","submitted_at":"2026-08-12T14:07:09Z","title":"NAE: Normalizing AutoEncoder","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-16T00:22:07.624836Z"},"links":{"cited_paper":"/paper/2106.09785","citing_paper":"/paper/2608.12084"},"observation_digest":"sha256:3015d68f5ae27fb99f7aa4bd0fcdb8a133d981ad37f804452517befb31fc04bd","observation_id":"7e36be43-e386-4aeb-b486-5a5db272fb61","resolution":{"observed_at":"2026-08-16T00:22:07.624836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2106.09785/citation-record","integrity":"/paper/2106.09785/integrity","json":"/paper/2106.09785/citation-record.json","paper":"/paper/2106.09785"},"outbound":[],"paper":{"arxiv_id":"2106.09785","last_updated":"2022-07-06T18:56:54Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T15:24:23.046977Z","submitted_at":"2021-06-17T19:57:33Z","title":"Efficient Self-supervised Vision Transformers for Representation Learning"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.09785."}