{"as_of":"2026-08-11T15:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:db48a376225e8f7a7e33b45807c5f00e3f66f079101ffe727d53b3b7e6b6215e","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":"2026-08-11T06:34:44.6726+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":"2026-08-11T00:52:23.006198Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":2,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.15351","last_updated":"2024-12-26T13:14:16Z","snapshot_observed_at":"2026-07-06T17:34:36.824374Z","submitted_at":"2024-02-23T14:38:19Z","title":"AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.15351","snapshot_observed_at":"2026-08-11T00:52:23.006198Z","title":"Autommlab: Automatically generating de- ployable models from language instructions for computer vi- sion tasks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19206","last_updated":"2024-12-26T13:07:03Z","snapshot_observed_at":"2026-08-11T00:47:56.417413Z","submitted_at":"2024-12-26T13:07:03Z","title":"NADER: Neural Architecture Design via Multi-Agent Collaboration","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T00:52:23.006198Z"},"links":{"cited_paper":"/paper/2402.15351","citing_paper":"/paper/2412.19206"},"observation_digest":"sha256:6e2a82e9dbabb371fb0c72a14e91406bb4fbb70c9bc5b45cee86e0e0cef5b60a","observation_id":"9dead06f-7f62-4a35-996f-cdfc7691b96c","resolution":{"observed_at":"2026-08-11T00:52:23.006198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.15351","last_updated":"2024-12-26T13:14:16Z","snapshot_observed_at":"2026-07-06T17:34:36.824374Z","submitted_at":"2024-02-23T14:38:19Z","title":"AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision Tasks","version":2},"cited_work":{"arxiv_id":"2402.15351","doi":"10.48550/arxiv.2402.15351","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.15351","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi:10.48550/arXiv.2402.15351 , abstract =","venue":"arXiv (Cornell University)","work_id":"9a4105be-4b79-4316-9c81-e795aa2c5241","year":null},"citing_paper":{"arxiv_id":"2606.20728","last_updated":"2026-06-17T04:52:22Z","snapshot_observed_at":"2026-08-03T01:36:23.956876Z","submitted_at":"2026-06-17T04:52:22Z","title":"VTOS: Learning to Orchestrate Vision Tools by Co-Searching Solutions and Observers","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-06-26T21:36:17.228002Z"},"links":{"cited_paper":"/paper/2402.15351","citing_paper":"/paper/2606.20728"},"observation_digest":"sha256:631b4412b0c82ec72365068b3a08ee481e2cd3deecaa63951fb1e43ebeb602a6","observation_id":"a625f94b-a15b-456b-9657-d60328cbe91e","resolution":{"observed_at":"2026-06-26T21:40:08.311451Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.15351/citation-record","integrity":"/paper/2402.15351/integrity","json":"/paper/2402.15351/citation-record.json","paper":"/paper/2402.15351"},"outbound":[],"paper":{"arxiv_id":"2402.15351","last_updated":"2024-12-26T13:14:16Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T17:34:36.824374Z","submitted_at":"2024-02-23T14:38:19Z","title":"AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision Tasks"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.15351."}