{"as_of":"2026-08-10T13:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:04b752cddc619e9d26e6d5f170b97b9b747566c886cd24ed367e25495354ba60","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T20:08:57.270395Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T01:27:31.075443Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":"2108.01624","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-07-03T01:27:31.075443Z","title":"Large-scale differentially private bert","venue":null,"work_id":"42d46873-b36f-49fe-bd2b-e2fee8d02f56","year":2021},"citing_paper":{"arxiv_id":"2202.07646","last_updated":"2023-03-06T06:28:18Z","snapshot_observed_at":"2026-08-03T19:51:05.627063Z","submitted_at":"2022-02-15T18:48:31Z","title":"Quantifying Memorization Across Neural Language Models","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-13T22:04:59.678438Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2202.07646"},"observation_digest":"sha256:1b6b84174242891fd9c2accc8b72158fb080f7228f32d960de1dbc5614d88210","observation_id":"25166d02-c32b-4371-b99a-639ec4dca86d","resolution":{"observed_at":"2026-05-13T22:04:59.719858Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":"2108.01624","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-07-03T01:27:31.075443Z","title":"Large-scale differentially private bert","venue":null,"work_id":"42d46873-b36f-49fe-bd2b-e2fee8d02f56","year":2021},"citing_paper":{"arxiv_id":"2304.01373","last_updated":"2023-05-31T17:54:07Z","snapshot_observed_at":"2026-08-07T23:49:29.478548Z","submitted_at":"2023-04-03T20:58:15Z","title":"Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling","version":2},"reference_index":224,"source":"arxiv_source","source_observed_at":"2026-05-15T17:45:17.540282Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2304.01373"},"observation_digest":"sha256:63308409e5f2deb6244f974cf7cacb8e2fdc362dea10f8acfb697a858595c7b7","observation_id":"29b8f53e-8efe-4ffc-8fd5-de82409646e7","resolution":{"observed_at":"2026-05-15T17:45:17.942185Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-08-08T20:08:57.270395Z","title":"Large-scale differentially private bert","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.05159","last_updated":"2025-05-27T16:54:17Z","snapshot_observed_at":"2026-08-09T21:49:24.558670Z","submitted_at":"2025-02-07T18:41:21Z","title":"A Lightweight Method to Disrupt Memorized Sequences in LLM","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-08T20:08:57.270395Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2502.05159"},"observation_digest":"sha256:3259e977ab20400b4a1c9b934c83774db9559ee7f7ad2c54b141918a52f443c4","observation_id":"807bf33c-57d7-452b-9f79-7ea34005f6ae","resolution":{"observed_at":"2026-08-08T20:08:57.270395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-08-07T04:33:16.813407Z","title":"Large-scale differentially pri- vate bert","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10424","last_updated":"2025-06-12T07:23:56Z","snapshot_observed_at":"2026-08-08T16:23:05.158098Z","submitted_at":"2025-06-12T07:23:56Z","title":"SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:33:16.813407Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2506.10424"},"observation_digest":"sha256:4d94f3b6939661a4b67ff94902d1ef67b8da75cc4a5f4751bb67ed64b4b891cf","observation_id":"40ba1c93-4b24-4713-b47a-4c5a8363e815","resolution":{"observed_at":"2026-08-07T04:33:16.813407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-08-06T21:06:00.814361Z","title":"Large-scale differentially private bert","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.01154","last_updated":"2025-07-01T19:28:37Z","snapshot_observed_at":"2026-08-09T17:44:37.427174Z","submitted_at":"2025-07-01T19:28:37Z","title":"FlashDP: Private Training Large Language Models with Efficient DP-SGD","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T21:06:00.814361Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2507.01154"},"observation_digest":"sha256:018c238f0f0624f197ab5bc4aafe04a1ec29cdd3c5580eef9e029f57dc7e80d7","observation_id":"fe8390a5-d080-424e-a9b5-434193777d07","resolution":{"observed_at":"2026-08-06T21:06:00.814361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":"2108.01624","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-07-03T01:27:31.075443Z","title":"Large-scale differentially private bert","venue":null,"work_id":"42d46873-b36f-49fe-bd2b-e2fee8d02f56","year":2021},"citing_paper":{"arxiv_id":"2601.10237","last_updated":"2026-04-16T13:16:57Z","snapshot_observed_at":"2026-07-30T08:45:45.642515Z","submitted_at":"2026-01-15T09:50:36Z","title":"Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-16T13:37:50.765735Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2601.10237"},"observation_digest":"sha256:489b4e45c59e44db9dacd9708ad8970f674d122d5e0b82f3788dd03e9fd2e374","observation_id":"5aa0ad4d-1028-47ba-932a-820e5293f6e3","resolution":{"observed_at":"2026-05-16T13:37:56.542875Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT","version":1},"cited_work":{"arxiv_id":"2108.01624","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2108.01624","snapshot_observed_at":"2026-07-03T01:27:31.075443Z","title":"Large-scale differentially private bert","venue":null,"work_id":"42d46873-b36f-49fe-bd2b-e2fee8d02f56","year":2021},"citing_paper":{"arxiv_id":"2606.09125","last_updated":"2026-06-08T07:19:42Z","snapshot_observed_at":"2026-07-06T23:48:30.569726Z","submitted_at":"2026-06-08T07:19:42Z","title":"Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-06-27T16:33:28.848573Z"},"links":{"cited_paper":"/paper/2108.01624","citing_paper":"/paper/2606.09125"},"observation_digest":"sha256:1cb045da5e31d5dfb5ddb3e9f5f2eed8828e80f477fd8e346c6ca1f1a06a1c86","observation_id":"1fb76b8c-0167-4009-8b53-7b9d9d87407b","resolution":{"observed_at":"2026-07-03T01:27:31.076788Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2108.01624/citation-record","integrity":"/paper/2108.01624/integrity","json":"/paper/2108.01624/citation-record.json","paper":"/paper/2108.01624"},"outbound":[],"paper":{"arxiv_id":"2108.01624","last_updated":"2021-08-03T16:51:36Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T08:29:42.386788Z","submitted_at":"2021-08-03T16:51:36Z","title":"Large-Scale Differentially Private BERT"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2108.01624."}