{"as_of":"2026-08-08T11:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:585a216ad2463eba70f3601b29682d33afa05281d19bc534ab76cdc044f0de39","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T05:14:34.775259Z","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":"2026-07-04T09:09:43.090600Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.01646","last_updated":"2024-06-19T04:48:13Z","snapshot_observed_at":"2026-07-06T15:50:06.784435Z","submitted_at":"2023-07-04T10:58:42Z","title":"SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.01646","snapshot_observed_at":"2026-08-07T05:14:34.775259Z","title":"Swingnn: Rethink- ing permutation invariance in diffusion models for graph generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08541","last_updated":"2025-07-05T09:04:57Z","snapshot_observed_at":"2026-08-07T05:05:21.366726Z","submitted_at":"2025-06-10T08:08:31Z","title":"TrajFlow: Multi-modal Motion Prediction via Flow Matching","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:34.775259Z"},"links":{"cited_paper":"/paper/2307.01646","citing_paper":"/paper/2506.08541"},"observation_digest":"sha256:37326d9f54fc20549a6e3ecd8931c5bf8c7a24c948d56ef98dd4377f44b0aaf1","observation_id":"8be9468f-c827-492b-84d6-ffd6b17ee269","resolution":{"observed_at":"2026-08-07T05:14:34.775259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.01646","last_updated":"2024-06-19T04:48:13Z","snapshot_observed_at":"2026-07-06T15:50:06.784435Z","submitted_at":"2023-07-04T10:58:42Z","title":"SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation","version":4},"cited_work":{"arxiv_id":"2307.01646","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.01646","snapshot_observed_at":"2026-07-04T09:09:43.090600Z","title":"Swingnn: Rethinking permutation invariance in diffusion models for graph generation.arXiv preprint arXiv:2307.01646,","venue":null,"work_id":"48d03221-d58f-49f9-8211-ff741102a4ac","year":null},"citing_paper":{"arxiv_id":"2606.22702","last_updated":"2026-06-21T22:38:35Z","snapshot_observed_at":"2026-08-04T23:28:45.231859Z","submitted_at":"2026-06-21T22:38:35Z","title":"Modular Diffusion Models for Structured Visual Recognition","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-26T10:29:04.711627Z"},"links":{"cited_paper":"/paper/2307.01646","citing_paper":"/paper/2606.22702"},"observation_digest":"sha256:f2f65dddf975130d63739cc45824e696a596c64fc865bb43e637f68c0c628798","observation_id":"adea071c-f83a-4c74-a111-b0cf0f8ef389","resolution":{"observed_at":"2026-07-04T09:09:43.092494Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2307.01646/citation-record","integrity":"/paper/2307.01646/integrity","json":"/paper/2307.01646/citation-record.json","paper":"/paper/2307.01646"},"outbound":[],"paper":{"arxiv_id":"2307.01646","last_updated":"2024-06-19T04:48:13Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T15:50:06.784435Z","submitted_at":"2023-07-04T10:58:42Z","title":"SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.01646."}