{"as_of":"2026-08-13T17:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1a1de95cda1373b27586209846e55442c8c51bc681c82ab0c78a7624530bd4da","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T15:15:22.755707Z","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":"2026-05-10T13:20:26.689575Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2208.13138","last_updated":"2022-08-28T04:18:27Z","snapshot_observed_at":"2026-08-13T14:37:54.154430Z","submitted_at":"2022-08-28T04:18:27Z","title":"ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.13138","snapshot_observed_at":"2026-08-12T15:15:22.755707Z","title":"Clustr: Exploring efficient self-attention via clustering for vision transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.14429","last_updated":"2024-11-21T18:59:08Z","snapshot_observed_at":"2026-08-12T15:09:04.988010Z","submitted_at":"2024-11-21T18:59:08Z","title":"Revisiting the Integration of Convolution and Attention for Vision Backbone","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-12T15:15:22.755707Z"},"links":{"cited_paper":"/paper/2208.13138","citing_paper":"/paper/2411.14429"},"observation_digest":"sha256:473776fe7192a4a5bbf57a372d6fe4e74b24165b1302d23940ce882ba18d7c11","observation_id":"c57ac0cd-f838-4904-b964-df1166874530","resolution":{"observed_at":"2026-08-12T15:15:22.755707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.13138","last_updated":"2022-08-28T04:18:27Z","snapshot_observed_at":"2026-08-13T14:37:54.154430Z","submitted_at":"2022-08-28T04:18:27Z","title":"ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers","version":1},"cited_work":{"arxiv_id":"2208.13138","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2208.13138","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"8eb4f714-83cd-4be8-a4d8-5d8858e77c80","year":2022},"citing_paper":{"arxiv_id":"2604.13432","last_updated":"2026-04-15T03:06:24Z","snapshot_observed_at":"2026-08-11T07:22:51.165686Z","submitted_at":"2026-04-15T03:06:24Z","title":"MaMe & MaRe: Matrix-Based Token Merging and Restoration for Efficient Visual Perception and Synthesis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T13:06:09.392876Z"},"links":{"cited_paper":"/paper/2208.13138","citing_paper":"/paper/2604.13432"},"observation_digest":"sha256:a54c701ed7c800285c25d466e7c74661b23030ff71a3af49be49a9b4cbf1fb0e","observation_id":"c015c538-e9b1-4155-b3d5-4ff0a84f0341","resolution":{"observed_at":"2026-05-10T13:20:26.691101Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2208.13138/citation-record","integrity":"/paper/2208.13138/integrity","json":"/paper/2208.13138/citation-record.json","paper":"/paper/2208.13138"},"outbound":[],"paper":{"arxiv_id":"2208.13138","last_updated":"2022-08-28T04:18:27Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T14:37:54.154430Z","submitted_at":"2022-08-28T04:18:27Z","title":"ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2208.13138."}