{"as_of":"2026-08-08T18:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9f8c721f6ae4eb8bdeb0f1d90cc089f7effb5decd2a7d6f9d34d4aaf4655402a","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:36:54.409871Z","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":"2026-08-06T18:36:54.538943Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.15596","last_updated":"2023-08-24T14:00:18Z","snapshot_observed_at":"2026-07-06T13:58:22.032846Z","submitted_at":"2022-09-30T17:19:40Z","title":"Individual Privacy Accounting with Gaussian Differential Privacy","version":2},"cited_work":{"arxiv_id":"2209.15596","doi":null,"metadata_source":"pith","pith_arxiv_id":"2209.15596","snapshot_observed_at":"2026-08-06T18:36:54.538943Z","title":"Individual Privacy Accounting with Gaussian Differential Privacy","venue":"cs.CR","work_id":"f8085f4f-d30f-4f73-8c79-b9e0aaec17f4","year":2022},"citing_paper":{"arxiv_id":"2507.08163","last_updated":"2025-07-10T20:52:22Z","snapshot_observed_at":"2026-08-06T18:23:12.006143Z","submitted_at":"2025-07-10T20:52:22Z","title":"Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T18:36:54.409871Z"},"links":{"cited_paper":"/paper/2209.15596","citing_paper":"/paper/2507.08163"},"observation_digest":"sha256:5414854969b8f71d24578dab3579d0744bac70a050db7d8a7a116ccdaf4ea61e","observation_id":"d9f5b578-e175-4c46-9678-835ccb787f3b","resolution":{"observed_at":"2026-08-06T18:36:54.543747Z","resolver_source":"local_arxiv","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/2209.15596/citation-record","integrity":"/paper/2209.15596/integrity","json":"/paper/2209.15596/citation-record.json","paper":"/paper/2209.15596"},"outbound":[],"paper":{"arxiv_id":"2209.15596","last_updated":"2023-08-24T14:00:18Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T13:58:22.032846Z","submitted_at":"2022-09-30T17:19:40Z","title":"Individual Privacy Accounting with Gaussian Differential Privacy"},"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 1 inbound Pith citation observation for arXiv:2209.15596."}