{"as_of":"2026-08-12T07:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f0047959e92995936bd0f5ba9e5f1107378d05d2a10b29be0c681edbb436834a","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":"2026-08-12T06:34:41.77262+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":"2026-08-11T12:07:16.609331Z","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":"2026-07-03T19:08:49.497393Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1702.01721","last_updated":"2017-02-06T17:47:08Z","snapshot_observed_at":"2026-07-06T05:28:58.882304Z","submitted_at":"2017-02-06T17:47:08Z","title":"View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.01721","snapshot_observed_at":"2026-08-11T12:07:16.609331Z","title":"Z., Shu, G., Ortiz, E., et al","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.14640","last_updated":"2025-01-01T18:00:00Z","snapshot_observed_at":"2026-08-11T14:41:39.744513Z","submitted_at":"2024-12-19T08:51:01Z","title":"Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learning","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-11T12:07:16.609331Z"},"links":{"cited_paper":"/paper/1702.01721","citing_paper":"/paper/2412.14640"},"observation_digest":"sha256:a058f11b17c427177147f14e76627eb9314749f17ffdab1a921e22af90952da4","observation_id":"924c429c-7d26-475b-8828-3176e8e94684","resolution":{"observed_at":"2026-08-11T12:07:16.609331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1702.01721","last_updated":"2017-02-06T17:47:08Z","snapshot_observed_at":"2026-07-06T05:28:58.882304Z","submitted_at":"2017-02-06T17:47:08Z","title":"View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network","version":1},"cited_work":{"arxiv_id":"1702.01721","doi":null,"metadata_source":"pith","pith_arxiv_id":"1702.01721","snapshot_observed_at":"2026-07-03T19:08:49.497393Z","title":"View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network","venue":"cs.CV","work_id":"9e09e820-8c45-407b-9e00-69642e1c235c","year":2017},"citing_paper":{"arxiv_id":"2606.17406","last_updated":"2026-06-16T01:41:07Z","snapshot_observed_at":"2026-07-06T23:53:02.028020Z","submitted_at":"2026-06-16T01:41:07Z","title":"Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-06-27T02:16:27.651526Z"},"links":{"cited_paper":"/paper/1702.01721","citing_paper":"/paper/2606.17406"},"observation_digest":"sha256:1b71b4c2fafc193aac0aff3cce825a04d0262e4b3d683057dd9d7245ab7b6650","observation_id":"0c1c588a-2249-4ee2-bbf7-72fa9c3ee17d","resolution":{"observed_at":"2026-07-03T19:08:49.499081Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1702.01721/citation-record","integrity":"/paper/1702.01721/integrity","json":"/paper/1702.01721/citation-record.json","paper":"/paper/1702.01721"},"outbound":[],"paper":{"arxiv_id":"1702.01721","last_updated":"2017-02-06T17:47:08Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T05:28:58.882304Z","submitted_at":"2017-02-06T17:47:08Z","title":"View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network"},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1702.01721."}