{"as_of":"2026-08-09T16:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:162d812887724556acf9c50567d1415804cf20dc76999a92f241c4580e435aa6","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":"2026-08-09T06:31:02.800959+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":"2026-08-04T23:41:53.514594Z","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":"2026-05-15T12:30:35.242791Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.06671","last_updated":"2025-06-30T07:49:21Z","snapshot_observed_at":"2026-08-07T17:18:48.974831Z","submitted_at":"2025-03-09T15:45:53Z","title":"Emulating Self-attention with Convolution for Efficient Image Super-Resolution","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06671","snapshot_observed_at":"2026-08-04T23:41:53.514594Z","title":"Emulating Self-attention with Con- volution for Efficient Image Super-Resolution,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.06442","last_updated":"2025-09-08T08:39:45Z","snapshot_observed_at":"2026-08-04T23:41:52.559474Z","submitted_at":"2025-09-08T08:39:45Z","title":"Perception-oriented Bidirectional Attention Network for Image Super-resolution Quality Assessment","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T23:41:53.514594Z"},"links":{"cited_paper":"/paper/2503.06671","citing_paper":"/paper/2509.06442"},"observation_digest":"sha256:00653bf13dff06537ba7a3fc7c3bad47239583dabb0db6f5162f183c1e41bec4","observation_id":"2aa78254-b0fa-4847-8a71-69c056d1a54f","resolution":{"observed_at":"2026-08-04T23:41:53.514594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06671","last_updated":"2025-06-30T07:49:21Z","snapshot_observed_at":"2026-08-07T17:18:48.974831Z","submitted_at":"2025-03-09T15:45:53Z","title":"Emulating Self-attention with Convolution for Efficient Image Super-Resolution","version":2},"cited_work":{"arxiv_id":"2503.06671","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.06671","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Emulat- ing self-attention with convolution for efficient image super- resolution","venue":null,"work_id":"45eea173-e225-469e-b99a-c37948dcb30c","year":2025},"citing_paper":{"arxiv_id":"2603.11680","last_updated":"2026-04-07T03:32:25Z","snapshot_observed_at":"2026-07-06T22:48:48.873215Z","submitted_at":"2026-03-12T08:46:19Z","title":"UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-15T12:30:22.351735Z"},"links":{"cited_paper":"/paper/2503.06671","citing_paper":"/paper/2603.11680"},"observation_digest":"sha256:3bddc76b49657d2ee43237b4b166e11eede5985037c1054cec2ed1a1e295892e","observation_id":"8888b47c-dabf-44e0-85fd-5cf39bc0ae25","resolution":{"observed_at":"2026-05-15T12:30:35.245648Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.06671/citation-record","integrity":"/paper/2503.06671/integrity","json":"/paper/2503.06671/citation-record.json","paper":"/paper/2503.06671"},"outbound":[],"paper":{"arxiv_id":"2503.06671","last_updated":"2025-06-30T07:49:21Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T17:18:48.974831Z","submitted_at":"2025-03-09T15:45:53Z","title":"Emulating Self-attention with Convolution for Efficient Image Super-Resolution"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.06671."}