{"as_of":"2026-08-21T22:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1759ab681bb68e94bea95e88709152f0402ff4a31559bb7f2f4ba8bd65b32b17","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":"2026-08-21T06:32:19.484+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":"2026-08-15T22:19:40.827639Z","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":"2026-07-04T08:09:41.016564Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2006.09430","last_updated":"2021-03-02T02:21:28Z","snapshot_observed_at":"2026-08-13T22:24:21.024923Z","submitted_at":"2020-06-16T18:23:00Z","title":"Wasserstein Embedding for Graph Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.09430","snapshot_observed_at":"2026-08-15T22:19:40.827639Z","title":"K., and Hoffmann, H","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.07575","last_updated":"2025-05-15T16:50:52Z","snapshot_observed_at":"2026-08-19T22:45:34.771349Z","submitted_at":"2025-05-12T13:54:55Z","title":"Personalized Federated Learning under Model Dissimilarity Constraints","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T22:19:40.827639Z"},"links":{"cited_paper":"/paper/2006.09430","citing_paper":"/paper/2505.07575"},"observation_digest":"sha256:9dbc69e0bd6f45fc79d49706e80aabadd1fcf2aa25b72abcf3a7dd1613c33822","observation_id":"ccb22c00-773a-43b2-88a4-333ece985705","resolution":{"observed_at":"2026-08-15T22:19:40.827639Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.09430","last_updated":"2021-03-02T02:21:28Z","snapshot_observed_at":"2026-08-13T22:24:21.024923Z","submitted_at":"2020-06-16T18:23:00Z","title":"Wasserstein Embedding for Graph Learning","version":2},"cited_work":{"arxiv_id":"2006.09430","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.09430","snapshot_observed_at":"2026-07-04T08:09:41.016564Z","title":"arXiv preprint arXiv:2006.09430 , year=","venue":null,"work_id":"fd2c84ae-3b2f-4cc5-9dc9-900f1f20116c","year":2006},"citing_paper":{"arxiv_id":"2606.21840","last_updated":"2026-06-20T02:15:54Z","snapshot_observed_at":"2026-08-10T03:36:54.731899Z","submitted_at":"2026-06-20T02:15:54Z","title":"A Test for Treatment Heterogeneity under a Distributional Difference-in-Difference Framework","version":1},"reference_index":142,"source":"arxiv_source","source_observed_at":"2026-06-26T12:13:05.050596Z"},"links":{"cited_paper":"/paper/2006.09430","citing_paper":"/paper/2606.21840"},"observation_digest":"sha256:4fc58b094a9ba53e94876cdc45befd62a78db61049bf5173554114df6d2c0865","observation_id":"d678f668-6838-41bd-b305-3797077c0631","resolution":{"observed_at":"2026-07-04T08:09:41.017986Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2006.09430/citation-record","integrity":"/paper/2006.09430/integrity","json":"/paper/2006.09430/citation-record.json","paper":"/paper/2006.09430"},"outbound":[],"paper":{"arxiv_id":"2006.09430","last_updated":"2021-03-02T02:21:28Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T22:24:21.024923Z","submitted_at":"2020-06-16T18:23:00Z","title":"Wasserstein Embedding for Graph Learning"},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2006.09430."}