{"as_of":"2026-08-20T02:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1062aa667bd39271c8d19e8604bb7eec6b9e913a1c1ac832c880cadc12235703","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T14:11:39.681454Z","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":"2026-08-11T14:11:28.385494Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.19128","last_updated":"2024-10-01T18:40:07Z","snapshot_observed_at":"2026-08-16T13:14:38.550698Z","submitted_at":"2024-09-27T20:21:19Z","title":"Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models","version":2},"cited_work":{"arxiv_id":"2409.19128","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.19128","snapshot_observed_at":"2026-08-11T14:11:28.385494Z","title":"Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models","venue":"cs.CV","work_id":"5a25541f-08ed-413d-ab4e-50c309ee1203","year":2024},"citing_paper":{"arxiv_id":"2412.12441","last_updated":"2024-12-17T01:09:23Z","snapshot_observed_at":"2026-08-16T13:20:46.681231Z","submitted_at":"2024-12-17T01:09:23Z","title":"Numerical Pruning for Efficient Autoregressive Models","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-11T14:11:27.137494Z"},"links":{"cited_paper":"/paper/2409.19128","citing_paper":"/paper/2412.12441"},"observation_digest":"sha256:20303bc93f46008bb40f924b94f9292bdfe9626f6ccb6bae88951bac8420f11c","observation_id":"82c8a359-0168-4af6-b815-45a67f823c4a","resolution":{"observed_at":"2026-08-11T14:11:28.389739Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19128","last_updated":"2024-10-01T18:40:07Z","snapshot_observed_at":"2026-08-16T13:14:38.550698Z","submitted_at":"2024-09-27T20:21:19Z","title":"Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.19128","snapshot_observed_at":"2026-08-11T14:11:39.681454Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12444","last_updated":"2025-03-21T15:52:39Z","snapshot_observed_at":"2026-08-16T12:25:35.685966Z","submitted_at":"2024-12-17T01:12:35Z","title":"LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers","version":3},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-11T14:11:39.681454Z"},"links":{"cited_paper":"/paper/2409.19128","citing_paper":"/paper/2412.12444"},"observation_digest":"sha256:2e705058d71030d914810c95ea401f9ee2344b43c3e427b9139a011ccc7c9c73","observation_id":"acc4d038-c9a8-4bf3-bac6-a0c902a364a7","resolution":{"observed_at":"2026-08-11T14:11:39.681454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19128","last_updated":"2024-10-01T18:40:07Z","snapshot_observed_at":"2026-08-16T13:14:38.550698Z","submitted_at":"2024-09-27T20:21:19Z","title":"Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.19128","snapshot_observed_at":"2026-08-03T02:34:19.490475Z","title":"Pruning then reweighting: Towards data- efficient training of diffusion models.arXiv preprint arXiv:2409.19128,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.17205","last_updated":"2026-07-30T22:57:15Z","snapshot_observed_at":"2026-08-13T15:58:10.431583Z","submitted_at":"2026-03-17T23:11:45Z","title":"OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T02:34:19.490475Z"},"links":{"cited_paper":"/paper/2409.19128","citing_paper":"/paper/2603.17205"},"observation_digest":"sha256:0396ba0ff85b276fe1ea1721a68d2bb8d5695a99fb279894a5d920799b631f0f","observation_id":"ac99a121-77f9-4c14-aa72-b2e2383b5500","resolution":{"observed_at":"2026-08-03T02:34:19.490475Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2409.19128/citation-record","integrity":"/paper/2409.19128/integrity","json":"/paper/2409.19128/citation-record.json","paper":"/paper/2409.19128"},"outbound":[],"paper":{"arxiv_id":"2409.19128","last_updated":"2024-10-01T18:40:07Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T13:14:38.550698Z","submitted_at":"2024-09-27T20:21:19Z","title":"Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.19128."}