{"as_of":"2026-08-08T12:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:66c5cbe5678bbb49dd2d9e02be4b1239583c268035080c73127fc6353507374b","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":"2026-08-07T14:14:20.444433Z","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":8,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.19518","last_updated":"2023-12-02T07:30:10Z","snapshot_observed_at":"2026-07-06T15:35:45.200564Z","submitted_at":"2023-05-31T03:01:36Z","title":"Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels","version":2},"cited_work":{"arxiv_id":"2305.19518","doi":"10.48550/arxiv.2305.19518","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.19518","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"arXiv (Cornell University)","work_id":"49cd8dd8-a99f-412a-a53c-1be18da81120","year":2023},"citing_paper":{"arxiv_id":"2405.12969","last_updated":"2026-05-11T07:50:55Z","snapshot_observed_at":"2026-07-06T18:17:25.642584Z","submitted_at":"2024-05-21T17:49:10Z","title":"EchoAlign: Bridging Generative and Discriminative Learning under Noisy Labels","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-24T01:14:56.879243Z"},"links":{"cited_paper":"/paper/2305.19518","citing_paper":"/paper/2405.12969"},"observation_digest":"sha256:13a9b850ee378e7cabd4f9afdabe8197dbceeb2394c874301ac96f805d78a545","observation_id":"15f753ce-ac16-4b89-8da3-b5bcf88dae8d","resolution":{"observed_at":"2026-05-24T01:15:54.230051Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2305.19518","last_updated":"2023-12-02T07:30:10Z","snapshot_observed_at":"2026-07-06T15:35:45.200564Z","submitted_at":"2023-05-31T03:01:36Z","title":"Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.19518","snapshot_observed_at":"2026-08-07T14:14:20.444433Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19675","last_updated":"2025-06-20T16:24:07Z","snapshot_observed_at":"2026-08-08T10:39:43.397796Z","submitted_at":"2025-05-26T08:31:55Z","title":"Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:14:20.444433Z"},"links":{"cited_paper":"/paper/2305.19518","citing_paper":"/paper/2505.19675"},"observation_digest":"sha256:273f951bf6baf1f64cc1fd1466f87389570401c4d1cec5c4b8df3202abbf3f39","observation_id":"fbfc0e05-d5b4-4745-8034-81ebb8248d06","resolution":{"observed_at":"2026-08-07T14:14:20.444433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2305.19518/citation-record","integrity":"/paper/2305.19518/integrity","json":"/paper/2305.19518/citation-record.json","paper":"/paper/2305.19518"},"outbound":[],"paper":{"arxiv_id":"2305.19518","last_updated":"2023-12-02T07:30:10Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T15:35:45.200564Z","submitted_at":"2023-05-31T03:01:36Z","title":"Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels"},"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:2305.19518."}