{"as_of":"2026-08-07T10:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a8c2f5db4e9243a14ebd856c241deb68f8c6ce3fae3383c7a3f83451013df204","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T22:42:45.396380Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.06647/citation-record","integrity":"/paper/2508.06647/integrity","json":"/paper/2508.06647/citation-record.json","paper":"/paper/2508.06647"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:42.977150Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:42.977150Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:0804ef9c6627710c4217076f1bbadc408fdb2fd5f29da4635dd1d8b42170addc","observation_id":"7a1dca4f-5e68-4ac8-b296-0d9a5cd7cb0f","resolution":{"observed_at":"2026-08-05T22:42:42.977150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.427481Z","title":"Cohen, Owen Daniel, Andrew Elliott, James Geddes, Callum Mole, Camila Rangel-Smith, and Lukasz Szpruch","venue":null,"work_id":"83e61258-4ea3-4f4e-a06f-f6d7e4d8acdb","year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.054887Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:c90f2917fd3b816464528a9f909cac936a9544cf799ee6934da5ea2240cccbe2","observation_id":"9ce1d844-4aee-4c43-8224-6d583d328b25","resolution":{"observed_at":"2026-08-05T22:42:46.432319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2760/50072","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:45.461916Z","title":null,"venue":null,"work_id":"22719136-ef2e-4078-aa77-3cc02785e070","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.214682Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:4b027becc4da6115b8e7d0e9ecf08aab042b88b4f4c3f9420b9b92b7802de968","observation_id":"93a45f16-5707-41c1-af9c-8dea56f2bde2","resolution":{"observed_at":"2026-08-05T22:42:45.465950Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02106","last_updated":"2023-08-05T06:28:12Z","snapshot_observed_at":"2026-07-06T15:50:26.113234Z","submitted_at":"2023-07-05T08:29:31Z","title":"SoK: Privacy-Preserving Data Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02106","snapshot_observed_at":"2026-08-05T22:42:43.317798Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.317798Z"},"links":{"cited_paper":"/paper/2307.02106","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:6fc112e8ba703ad6fde80e314ce52962fea579cdce17715215fda54d687349cc","observation_id":"a4c380b0-89c1-40ce-ae6b-52dc9e53fc51","resolution":{"observed_at":"2026-08-05T22:42:43.317798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08114","last_updated":"2022-08-25T07:28:50Z","snapshot_observed_at":"2026-07-06T13:42:36.328169Z","submitted_at":"2022-08-17T07:09:08Z","title":"An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models","version":2},"cited_work":{"arxiv_id":"2208.08114","doi":null,"metadata_source":"pith","pith_arxiv_id":"2208.08114","snapshot_observed_at":"2026-08-05T22:42:46.003271Z","title":"An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models","venue":"cs.CR","work_id":"99f28817-cd55-4283-bfd4-a736f4dcc145","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.403593Z"},"links":{"cited_paper":"/paper/2208.08114","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:90b1143d1f3197546399aaa86ee7f96e42faf052a59ac7436a815471fb097a74","observation_id":"09732801-7655-477e-aaa2-7929757ace71","resolution":{"observed_at":"2026-08-05T22:42:46.007904Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.413918Z","title":null,"venue":null,"work_id":"44e51408-b74e-47f3-85a9-03557439b41f","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.526100Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:64b023ab879188bb8ce20965718be13a26bbb5a2c99536a2eead203e4bfd48a7","observation_id":"2a7527b5-27c8-472c-90ec-dfcf7a6841bb","resolution":{"observed_at":"2026-08-05T22:42:46.418245Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.400740Z","title":null,"venue":null,"work_id":"721167a8-e5d2-4816-9221-74630127e996","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.579680Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:0b801807819923dea44b3e68bb883ecf37249a99ed68b04e73cfab62cfc838cd","observation_id":"0fd46697-b20b-462f-a7c4-a5f3094349a4","resolution":{"observed_at":"2026-08-05T22:42:46.404783Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13428","last_updated":"2024-11-20T16:11:20Z","snapshot_observed_at":"2026-08-05T08:53:25.018860Z","submitted_at":"2024-11-20T16:11:20Z","title":"SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers","version":1},"cited_work":{"arxiv_id":"2411.13428","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.13428","snapshot_observed_at":"2026-08-05T22:42:45.982543Z","title":"SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers","venue":"cs.LG","work_id":"e44bf82b-60ee-46ef-822c-7007379c46d3","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.689698Z"},"links":{"cited_paper":"/paper/2411.13428","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:3a76ec1d8216bb658ae2f2071d06e89d1e0f3829be1ad961aa478f6ab9a0c566","observation_id":"e2e082c9-d183-444e-b927-8621f15ab782","resolution":{"observed_at":"2026-08-05T22:42:45.987069Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.387316Z","title":null,"venue":null,"work_id":"345046c6-4914-40ae-b757-24ec10d5b9bc","year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.767233Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:3502d03396563504c633c3af742a73559fcc5af4d1df36c694f3607a1a2b8891","observation_id":"4847b134-185b-4c44-a324-6c522e66f32e","resolution":{"observed_at":"2026-08-05T22:42:46.391430Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-05T22:42:43.880004Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.880004Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:9dafc94e36f299a3b01ec3b23f230c24ee98245bd0a22b0799396a9a61c0e2bc","observation_id":"cf5a8126-5c0a-49c4-916e-e36e887c2377","resolution":{"observed_at":"2026-08-05T22:42:43.880004Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.374120Z","title":null,"venue":null,"work_id":"4fb31639-a427-496f-a2f5-fee0f4309dc9","year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.951677Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:60e5b115901a3bd1a31ba46459ff0493631c91eb10538c1df3813140656538ce","observation_id":"695905f2-d6b0-46e9-9989-865deef7dcad","resolution":{"observed_at":"2026-08-05T22:42:46.378103Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09249","last_updated":"2021-02-18T10:11:29Z","snapshot_observed_at":"2026-07-06T10:42:28.724054Z","submitted_at":"2021-02-18T10:11:29Z","title":"Composable Generative Models","version":1},"cited_work":{"arxiv_id":"2102.09249","doi":null,"metadata_source":"pith","pith_arxiv_id":"2102.09249","snapshot_observed_at":"2026-08-05T22:42:45.945892Z","title":"Composable Generative Models","venue":"cs.LG","work_id":"61b02ec9-4003-427e-935b-539cc92a7ea2","year":2021},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.035597Z"},"links":{"cited_paper":"/paper/2102.09249","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:bc55acff3d52c741dfb0e2140fc173928441378d7e17839a950cd43cf69e8aca","observation_id":"3de0ef3f-fb53-4329-8501-b6c379660748","resolution":{"observed_at":"2026-08-05T22:42:45.950398Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.360293Z","title":null,"venue":null,"work_id":"4380fa76-70e2-4d61-92fc-08982ab70d38","year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.098655Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:29c47209c0450d7b11f7f3a3a4a40f46d9f25eefa4fd29e39ddb469afef37da5","observation_id":"88fc4d37-dcb1-4ca9-906c-5ddd781c4a44","resolution":{"observed_at":"2026-08-05T22:42:46.364670Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.346474Z","title":null,"venue":null,"work_id":"7aa6f517-b755-4d2d-a6a8-60e32bf773c4","year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.163462Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:dbb0ab0df97bfeef67a490ccff9ef8b97acca9f2ff0216b39123455fc3a8576c","observation_id":"c58df8d6-7f40-4a19-adc3-e5ebd5694a9c","resolution":{"observed_at":"2026-08-05T22:42:46.350669Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.333263Z","title":null,"venue":null,"work_id":"86ab5621-110b-4396-97d7-fcc088eb9f59","year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.286354Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:8ed21fff67324ff6bdaa1d5d0ec7aab30dad475316943c6d9c972a78a1e5baab","observation_id":"f2e8eb5d-afb7-4c9f-adb0-c05c87504183","resolution":{"observed_at":"2026-08-05T22:42:46.337340Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.05216","last_updated":"2024-06-07T18:59:37Z","snapshot_observed_at":"2026-08-04T10:26:49.355032Z","submitted_at":"2024-06-07T18:59:37Z","title":"TabPFGen -- Tabular Data Generation with TabPFN","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.05216","snapshot_observed_at":"2026-08-05T22:42:44.385662Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.385662Z"},"links":{"cited_paper":"/paper/2406.05216","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:bb4b5d4958dcbb608ff9355b68bb225306cd52bd63d30c83f713a6006fa4317b","observation_id":"6ae195fb-4dee-44a6-b3d2-15a6e9ce94ee","resolution":{"observed_at":"2026-08-05T22:42:44.385662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.05593","last_updated":"2025-07-23T03:16:46Z","snapshot_observed_at":"2026-08-03T03:47:05.225758Z","submitted_at":"2024-07-08T04:15:43Z","title":"Unmasking Trees for Tabular Data","version":5},"cited_work":{"arxiv_id":"2407.05593","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.05593","snapshot_observed_at":"2026-08-05T22:42:45.908864Z","title":"Unmasking Trees for Tabular Data","venue":"cs.LG","work_id":"8a782659-af6b-4446-9938-9469cabe7d24","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.429740Z"},"links":{"cited_paper":"/paper/2407.05593","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:f439c54f011c12290ec453cef536ede8cf9850c832fa87f62987aae581d54771","observation_id":"46db6027-69ea-4738-80fa-c4ef5450248e","resolution":{"observed_at":"2026-08-05T22:42:45.913881Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.319719Z","title":null,"venue":null,"work_id":"368669e6-cc57-48b4-bfde-36357fe9ff14","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.527416Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:165b131a554f73d3ac031a754e00883f5656ee69d490b0ac2925706f6af3cc7a","observation_id":"f963c59f-fd4e-4657-8326-0bcd06ec40ce","resolution":{"observed_at":"2026-08-05T22:42:46.324092Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.306229Z","title":null,"venue":null,"work_id":"fe2fc45e-aef3-45b4-af6b-12d5fe57800a","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.575315Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:4a1188ed3c9df6d092383c15f3e9811f0a9eb5dd2442bcae02b1f70ab071bd2b","observation_id":"a39c17cb-e1ce-4a85-9609-404cbbabc4a7","resolution":{"observed_at":"2026-08-05T22:42:46.310484Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.292077Z","title":null,"venue":null,"work_id":"3479b7ea-f44d-4a32-a40d-297074571d0e","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.628801Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:c2752ed64b689b334b99a7b5f529b4c5f35992b13cbc745bddb423f5418a4fe9","observation_id":"c280ad07-dfe5-4531-b12e-370c3df9cf04","resolution":{"observed_at":"2026-08-05T22:42:46.296090Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.277507Z","title":null,"venue":null,"work_id":"f45b9bad-fae1-4b91-871c-450054ad6408","year":2025},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.738739Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:cedd1725489c5d9e69cdc062d57acfdd757d9112d80ddb7f6f97bc617020b153","observation_id":"50a9e1e2-35c7-48ec-9191-2f69ca507c25","resolution":{"observed_at":"2026-08-05T22:42:46.282330Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:44.781419Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.781419Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:064a887bdc8e9f587d92c888b082a93410487a1aeaeb50cc8acd90c647f545f9","observation_id":"5f9902af-f456-4eb7-b082-ca020f8691d0","resolution":{"observed_at":"2026-08-05T22:42:44.781419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.03384","last_updated":"2018-07-02T19:20:02Z","snapshot_observed_at":"2026-08-04T17:07:26.080555Z","submitted_at":"2018-06-09T00:23:15Z","title":"Data Synthesis based on Generative Adversarial Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.03384","snapshot_observed_at":"2026-08-05T22:42:44.856199Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.856199Z"},"links":{"cited_paper":"/paper/1806.03384","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:03d620d947b99005a2d1f9b5c308406d758cabc3c497f5a58557ca0b4ab40e32","observation_id":"fc3a90b1-d09c-435b-b1ef-fc2903a915b8","resolution":{"observed_at":"2026-08-05T22:42:44.856199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.04980","last_updated":"2025-03-06T21:19:02Z","snapshot_observed_at":"2026-08-07T05:36:02.031155Z","submitted_at":"2025-03-06T21:19:02Z","title":"A Consensus Privacy Metrics Framework for Synthetic Data","version":1},"cited_work":{"arxiv_id":"2503.04980","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.04980","snapshot_observed_at":"2026-08-05T22:42:45.807498Z","title":"A Consensus Privacy Metrics Framework for Synthetic Data","venue":"cs.CR","work_id":"7ef69e57-87a6-4e9f-bf5f-e702512c8202","year":2025},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:44.954687Z"},"links":{"cited_paper":"/paper/2503.04980","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:72c266ef0a4242c6419c1382dfb76f0e353c4da31deb27f38c2a0258c3838c5f","observation_id":"198c9dc0-e974-4166-893d-8398265b69ba","resolution":{"observed_at":"2026-08-05T22:42:45.812016Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.263400Z","title":null,"venue":null,"work_id":"b9893e21-5a2b-4c34-95c9-c87cedfa080a","year":2021},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.007031Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:4026a7dafbc53f0ff3759b41c7df06a459d55f5fdeabdd8825a215c3177a34c2","observation_id":"64b61377-cf3d-4840-924c-5dda77a4b67e","resolution":{"observed_at":"2026-08-05T22:42:46.267576Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:45.068924Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.068924Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:11bab1cbd4b1415ab377a01f4b4ad002922aff81673e3f97a488447e6cd6fc32","observation_id":"91360b78-d307-4bcf-bfeb-bf9dca30116c","resolution":{"observed_at":"2026-08-05T22:42:45.068924Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.13554","last_updated":"2022-10-24T08:39:05Z","snapshot_observed_at":"2026-08-03T17:58:01.856623Z","submitted_at":"2022-05-26T18:00:02Z","title":"Training and Inference on Any-Order Autoregressive Models the Right Way","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.13554","snapshot_observed_at":"2026-08-05T22:42:45.172004Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.172004Z"},"links":{"cited_paper":"/paper/2205.13554","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:6f679e8b908d0afd9fe47c00a82eea06d2d90e3078770038eb02f26539cb0190","observation_id":"8bd1baa2-cc85-4434-8f71-9949c3cae665","resolution":{"observed_at":"2026-08-05T22:42:45.172004Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:45.264316Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.264316Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:8942d21c39f10263022bc3e72b6cebb1622712ccb24d74c2e9e91fcfccc9443d","observation_id":"ed001250-4d04-42ae-96df-50aae3f1b3b7","resolution":{"observed_at":"2026-08-05T22:42:45.264316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.249543Z","title":null,"venue":null,"work_id":"c0d5ba5d-86de-492a-9057-3a94d4998964","year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.282927Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:7afb6ce20903e2b982c15510728ffb18c4568401ef260a737aa11959606e34ae","observation_id":"32e92bc3-43b4-48fb-b548-5e271e853b54","resolution":{"observed_at":"2026-08-05T22:42:46.253633Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.02041","last_updated":"2023-02-04T00:32:50Z","snapshot_observed_at":"2026-08-04T15:44:49.370490Z","submitted_at":"2023-02-04T00:32:50Z","title":"REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.02041","snapshot_observed_at":"2026-08-05T22:42:45.291442Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.291442Z"},"links":{"cited_paper":"/paper/2302.02041","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:0841fbf91c6a9a04d4a110763c7b6d0eb4358eee2e9e229f5b8310a5273bff36","observation_id":"285b9980-f71b-4d74-b9f3-a07b0a3ba362","resolution":{"observed_at":"2026-08-05T22:42:45.291442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.218842Z","title":null,"venue":null,"work_id":"f9ce79b8-73ce-4816-b9c0-104a4b5c29c1","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.295821Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:44bfa7d67e23c8e04f37ebf087e71daa216d05ccd57e977fa4e81f5a2d2c40c5","observation_id":"91b4717c-4820-430a-9a7a-8551cf274494","resolution":{"observed_at":"2026-08-05T22:42:46.223247Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03941","last_updated":"2025-01-07T17:02:33Z","snapshot_observed_at":"2026-08-05T16:09:27.358903Z","submitted_at":"2025-01-07T17:02:33Z","title":"Synthetic Data Privacy Metrics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03941","snapshot_observed_at":"2026-08-05T22:42:45.302583Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.302583Z"},"links":{"cited_paper":"/paper/2501.03941","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:82a4973f820b27029fba510a58f66ac8acbed54f3f6afda449637ba6b096a670","observation_id":"840aa235-c913-4982-92ea-de5f1b66ea74","resolution":{"observed_at":"2026-08-05T22:42:45.302583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:45.306995Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.306995Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:e944b9ff64bc3776a4b4b23d113cc085ebbcad890d922195b70a220f2ad1c5da","observation_id":"d4075e38-6980-430f-8258-ccbff2e78cab","resolution":{"observed_at":"2026-08-05T22:42:45.306995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.204168Z","title":null,"venue":null,"work_id":"77c5ede1-bf3d-4212-b720-a93fb6c5c093","year":2016},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.310975Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:493c4a951d41669659120c9edc13711941c97a6ca73151e7c9fc99af123b8da5","observation_id":"44fa88fa-a03b-45e5-90fc-45050ca366bc","resolution":{"observed_at":"2026-08-05T22:42:46.208768Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12580","last_updated":"2023-02-24T11:27:39Z","snapshot_observed_at":"2026-08-02T17:31:30.856348Z","submitted_at":"2023-02-24T11:27:39Z","title":"Membership Inference Attacks against Synthetic Data through Overfitting Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12580","snapshot_observed_at":"2026-08-05T22:42:45.315052Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.315052Z"},"links":{"cited_paper":"/paper/2302.12580","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:7169cd5b111039b86f50f9a7bbe49be8b7f7c26b761d166ea4108457f61bdbc2","observation_id":"d3807bdc-53d9-471a-95f4-45ab95241879","resolution":{"observed_at":"2026-08-05T22:42:45.315052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.03722","last_updated":"2023-04-07T16:38:40Z","snapshot_observed_at":"2026-07-06T15:13:25.115722Z","submitted_at":"2023-04-07T16:38:40Z","title":"Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.03722","snapshot_observed_at":"2026-08-05T22:42:45.319255Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.319255Z"},"links":{"cited_paper":"/paper/2304.03722","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:4cf890397ce2a7ad9116bfa56d1f39e3103a42e13f75c3676ea687d7581e11b9","observation_id":"da6dac13-cc63-4be3-8435-0c66e30f0c48","resolution":{"observed_at":"2026-08-05T22:42:45.319255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.189015Z","title":null,"venue":null,"work_id":"2acf5503-7410-4154-9229-9de3f54ae6bc","year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.323477Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:8bdca1e82a1f68c0b4ec66b65ef09466c1f4e36d7be60188d3f36ec34e3787fe","observation_id":"80c68f7c-4382-45b9-9d7a-5fce67e3cdbd","resolution":{"observed_at":"2026-08-05T22:42:46.193207Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.159450Z","title":null,"venue":null,"work_id":"9719eff5-8ee9-40c5-b17e-963c2aa4fcb6","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.331943Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:8f95f8781c7341d6abb5ab6e4a2725c8149a1aadbaee85d12ed59b0904f678f9","observation_id":"42f5efd1-1d83-45de-acf3-f3d08f49c739","resolution":{"observed_at":"2026-08-05T22:42:46.163879Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02549","last_updated":"2025-06-02T21:47:55Z","snapshot_observed_at":"2026-08-03T13:16:42.501262Z","submitted_at":"2024-07-02T15:27:06Z","title":"Diffusion Models for Tabular Data Imputation and Synthetic Data Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02549","snapshot_observed_at":"2026-08-05T22:42:45.336335Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.336335Z"},"links":{"cited_paper":"/paper/2407.02549","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:3f244c0424d8f7a0e03e9c32cfa15f61ad381f2f783d9f46e68dacce632f3735","observation_id":"502cb3f2-68ea-40e6-a13e-95df227a6c9a","resolution":{"observed_at":"2026-08-05T22:42:45.336335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.24963/ijcai.2021/432","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:45.426771Z","title":null,"venue":null,"work_id":"f49a8b72-ad29-4546-991b-14913df6d8b1","year":2021},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.340340Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:cafe3a26d74eaf456a1766aa32c65db1dee3b9b12fa33eab3ad5844c62e2f830","observation_id":"728bbdf7-ef1a-4671-8010-0a8d6416be36","resolution":{"observed_at":"2026-08-05T22:42:45.432343Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.09435","last_updated":"2023-03-13T16:15:46Z","snapshot_observed_at":"2026-08-04T17:38:28.354541Z","submitted_at":"2022-05-19T09:50:25Z","title":"Adversarial random forests for density estimation and generative modeling","version":4},"cited_work":{"arxiv_id":"2205.09435","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.09435","snapshot_observed_at":"2026-08-05T22:42:45.576751Z","title":"Adversarial random forests for density estimation and generative modeling","venue":"stat.ML","work_id":"a09a0425-752a-4bbd-98fc-5cebc8c0c618","year":2022},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.344187Z"},"links":{"cited_paper":"/paper/2205.09435","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:3f22be7c221c1b630ae289fbc1d9b9a3316d67f30fee50cc3474973b4e7b4a26","observation_id":"a6445f4e-4423-4b24-9b63-c896c2e7abaa","resolution":{"observed_at":"2026-08-05T22:42:45.581298Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02027","last_updated":"2024-06-27T05:47:55Z","snapshot_observed_at":"2026-07-06T18:24:56.906947Z","submitted_at":"2024-06-04T07:06:06Z","title":"Inference Attacks: A Taxonomy, Survey, and Promising Directions","version":2},"cited_work":{"arxiv_id":"2406.02027","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.02027","snapshot_observed_at":"2026-08-05T22:42:45.556782Z","title":"Inference Attacks: A Taxonomy, Survey, and Promising Directions","venue":"cs.LG","work_id":"07c9a7b5-b414-4eb1-a445-c5c36141358c","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.348227Z"},"links":{"cited_paper":"/paper/2406.02027","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:01ee6f6c04a56fbdb9e04f12d2a3317a8dcc6b0b51687df68e5d05c79266fdab","observation_id":"52cc36bb-7b22-420d-910c-0791affc02cd","resolution":{"observed_at":"2026-08-05T22:42:45.561791Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.06739","last_updated":"2018-02-19T18:05:33Z","snapshot_observed_at":"2026-07-06T06:24:12.439943Z","submitted_at":"2018-02-19T18:05:33Z","title":"Differentially Private Generative Adversarial Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.06739","snapshot_observed_at":"2026-08-05T22:42:45.352144Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.352144Z"},"links":{"cited_paper":"/paper/1802.06739","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:906d6e8b6c974686d438a9f9131eed5d7f94489c9313a08f74af52099429126c","observation_id":"152f0733-ca2a-4649-8a37-6e5517f85e73","resolution":{"observed_at":"2026-08-05T22:42:45.352144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:45.356034Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.356034Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:6987cbd909c2f730fd64d2f1528d63a6d01ef811993aa638a481910b25509bc8","observation_id":"6edfafc3-f983-4d54-8f04-bc9c1246628c","resolution":{"observed_at":"2026-08-05T22:42:45.356034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.08237","last_updated":"2020-01-02T12:48:08Z","snapshot_observed_at":"2026-07-31T22:49:43.034741Z","submitted_at":"2019-06-19T17:35:48Z","title":"XLNet: Generalized Autoregressive Pretraining for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.08237","snapshot_observed_at":"2026-08-05T22:42:45.364858Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.364858Z"},"links":{"cited_paper":"/paper/1906.08237","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:42cbd66c03ca32386e1146f410e1e203e6b126362d198ba9b098ab3229c2e57f","observation_id":"7ce90756-cae9-4179-8308-016321c8f39d","resolution":{"observed_at":"2026-08-05T22:42:45.364858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.120682Z","title":null,"venue":null,"work_id":"c708a5e6-b9ab-48b1-a340-777716d75bb2","year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.369146Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:7ed7ec991d2d6ebf4126119b83e124020bb1ce4a667f8d6d4eb55df525f1a59e","observation_id":"a73b00de-63de-44e6-9eff-f3939d51e174","resolution":{"observed_at":"2026-08-05T22:42:46.124607Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.106381Z","title":null,"venue":null,"work_id":"f9d55c7f-9512-4d0d-b9de-afbeb3b54b79","year":2019},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.377132Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:a96ce1d599572350a001ce85e78d018db7a8930efcb8c727b4081a4b6eea4d8e","observation_id":"dac9da5f-6e5a-473e-b633-d347310a9e15","resolution":{"observed_at":"2026-08-05T22:42:46.110407Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21523","last_updated":"2024-10-28T20:49:26Z","snapshot_observed_at":"2026-08-04T02:00:25.290354Z","submitted_at":"2024-10-28T20:49:26Z","title":"Diffusion-nested Auto-Regressive Synthesis of Heterogeneous Tabular Data","version":1},"cited_work":{"arxiv_id":"2410.21523","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.21523","snapshot_observed_at":"2026-08-05T22:42:45.490654Z","title":"Diffusion-nested Auto-Regressive Synthesis of Heterogeneous Tabular Data","venue":"cs.LG","work_id":"9bad68af-49cc-4e7f-9130-eebefd4b6f54","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.380858Z"},"links":{"cited_paper":"/paper/2410.21523","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:0dce394cf93a8a61c93b0c578d579a12ded93f048f862047c0ca213a8f6a960e","observation_id":"63db95cb-bd87-4ad6-aea6-2879ac80faf8","resolution":{"observed_at":"2026-08-05T22:42:45.496286Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.092045Z","title":null,"venue":null,"work_id":"d8371bd9-b5b7-4d55-9d32-5db4921851b4","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.384737Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:11ec029ff80cbbd506201b9917e716547fcda20e82b7471cb79db9cc575565f7","observation_id":"1f770790-28c7-41cb-b924-03e1c23c9080","resolution":{"observed_at":"2026-08-05T22:42:46.096518Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.077772Z","title":null,"venue":null,"work_id":"4493809a-403e-4e91-bf93-6657a11bdfc0","year":2021},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.388727Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:857e105f06382bedd47ee2e001d7c2127b391a2474a97cd87d53023244f48abd","observation_id":"bc056bc6-14ed-42d6-88d5-219b2b0a4f3e","resolution":{"observed_at":"2026-08-05T22:42:46.082141Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.063317Z","title":null,"venue":null,"work_id":"6ffbccce-f915-43e6-8ab7-26f01a2f5545","year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.392598Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:39c4efb64ff2c25d40d957ee754e4d8e1826c99446684fcc6072a555140720c7","observation_id":"8cfa0744-d8f5-4f96-8191-22b6604ba6a9","resolution":{"observed_at":"2026-08-05T22:42:46.067567Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.049509Z","title":"��������� �� ��� ����6 (2024), 1296508","venue":null,"work_id":"0db6bfdf-2930-4b6b-bf4c-5911d5b0be0d","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.396380Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:b698cd1dfd2c13c80c069794bd500331f6166a22fb293822cb3562e04fdcef01","observation_id":"036ac567-dc40-4fe0-b99a-c5f7c66fe76a","resolution":{"observed_at":"2026-08-05T22:42:46.053595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.134815Z","title":null,"venue":null,"work_id":"31ac9f7a-6509-49bd-9448-b7489948b110","year":2019},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.360247Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:89f00d76f27b383261acea3771d14586fe7b98b541c19fe4e4c94f26309dfd06","observation_id":"8c52e46a-968c-4083-89f9-e9ade0db02ea","resolution":{"observed_at":"2026-08-05T22:42:46.138959Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.174326Z","title":"In �������� �� ������ ����������� ���������� �������, M","venue":null,"work_id":"9734f1e9-148c-4b4d-bdfd-b4e7a952df2f","year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.327546Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:8d6253d889f425960d34baea7dba6a013e581d69ba143de2312102f1ee5ae400","observation_id":"1389c955-e144-4fba-9ff2-8357dd94d11a","resolution":{"observed_at":"2026-08-05T22:42:46.178524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.06550","last_updated":"2022-11-12T02:26:54Z","snapshot_observed_at":"2026-07-06T14:17:23.153337Z","submitted_at":"2022-11-12T02:26:54Z","title":"TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.06550","snapshot_observed_at":"2026-08-05T22:42:43.147398Z","title":"arXiv:2211.06550 [cs.CR]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:43.147398Z"},"links":{"cited_paper":"/paper/2211.06550","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:49910ef7132e2fb16e25fc76f229c91e4fd4bce52c428b43b19749d4f9911dca","observation_id":"6da6c689-4e25-49fd-97e1-8c184ebbcf8f","resolution":{"observed_at":"2026-08-05T22:42:43.147398Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:42:46.234481Z","title":"����� ���� 7, 4 (2024), ooae114","venue":null,"work_id":"5786e6c3-b228-4bab-912f-6c2d01a3c759","year":2024},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.287314Z"},"links":{"citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:ef0b874946ff988ac83b063199d4b12d030d9d5131f2ba80e5e8072724ef2e86","observation_id":"7969f304-099a-42e7-8d90-8adfef2b574d","resolution":{"observed_at":"2026-08-05T22:42:46.238972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.01524","last_updated":"2025-05-02T18:21:14Z","snapshot_observed_at":"2026-08-05T17:51:32.570722Z","submitted_at":"2025-05-02T18:21:14Z","title":"The DCR Delusion: Measuring the Privacy Risk of Synthetic Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.01524","snapshot_observed_at":"2026-08-05T22:42:45.373036Z","title":"arXiv:2505.01524 [cs.CR]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-05T22:42:45.373036Z"},"links":{"cited_paper":"/paper/2505.01524","citing_paper":"/paper/2508.06647"},"observation_digest":"sha256:a3687b8b8d72c32b72028ba99f3daf8c4a79334db26c441c3fc6f55ed8c67d80","observation_id":"408a8c77-f4cc-4e90-a59c-68fb96c60357","resolution":{"observed_at":"2026-08-05T22:42:45.373036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2508.06647","last_updated":"2025-08-08T18:57:23Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T22:42:42.411406Z","submitted_at":"2025-08-08T18:57:23Z","title":"Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":2,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":42,"verified_exact":8,"verified_fuzzy":4},"total_outbound_references":57},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2508.06647."}