{"as_of":"2026-08-07T20:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:db10e5707be26fd502cdfcc0f38b977e3dfb94f01f4647ffe7b863ed96079b9c","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:13:58.334515Z","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":"2026-07-03T01:27:31.548927Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.01394","last_updated":"2025-05-28T12:38:37Z","snapshot_observed_at":"2026-07-06T18:24:30.706727Z","submitted_at":"2024-06-03T14:57:39Z","title":"PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01394","snapshot_observed_at":"2026-08-07T13:13:58.334515Z","title":"Priva- cyrestore: Privacy-preserving inference in large language models via privacy removal and restoration,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22311","last_updated":"2025-05-28T12:54:07Z","snapshot_observed_at":"2026-08-07T13:08:02.863373Z","submitted_at":"2025-05-28T12:54:07Z","title":"From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications","version":1},"reference_index":151,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:58.334515Z"},"links":{"cited_paper":"/paper/2406.01394","citing_paper":"/paper/2505.22311"},"observation_digest":"sha256:6ea175a1460ff2a3cabe8b495fc0c8dccc135d88a736309e3ec7bee6e8fca562","observation_id":"1b27c759-712d-4f21-9a98-5e60773cfca6","resolution":{"observed_at":"2026-08-07T13:13:58.334515Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01394","last_updated":"2025-05-28T12:38:37Z","snapshot_observed_at":"2026-07-06T18:24:30.706727Z","submitted_at":"2024-06-03T14:57:39Z","title":"PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01394","snapshot_observed_at":"2026-08-06T01:01:39.208973Z","title":"arXiv preprint arXiv:2406.01394","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03991","last_updated":"2025-08-06T00:46:38Z","snapshot_observed_at":"2026-08-07T15:24:25.018265Z","submitted_at":"2025-08-06T00:46:38Z","title":"Galaxy: A Cognition-Centered Framework for Proactive, Privacy-Preserving, and Self-Evolving LLM Agents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T01:01:39.208973Z"},"links":{"cited_paper":"/paper/2406.01394","citing_paper":"/paper/2508.03991"},"observation_digest":"sha256:8ce4cb12617a430c4ee9ba4f287cf7cc151eacb005db14b36a5c024b26375ab8","observation_id":"e8481138-b169-4045-a1cb-d5108e37b106","resolution":{"observed_at":"2026-08-06T01:01:39.208973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01394","last_updated":"2025-05-28T12:38:37Z","snapshot_observed_at":"2026-07-06T18:24:30.706727Z","submitted_at":"2024-06-03T14:57:39Z","title":"PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01394","snapshot_observed_at":"2026-08-05T22:58:28.517009Z","title":"Mingjin Zhang, Xiaoming Shen, Jiannong Cao, Zeyang Cui, and Shan Jiang","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.09194","last_updated":"2025-08-08T09:53:53Z","snapshot_observed_at":"2026-08-07T17:54:38.232851Z","submitted_at":"2025-08-08T09:53:53Z","title":"Meta-Learning for Speeding Up Large Model Inference in Decentralized Environments","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T22:58:28.517009Z"},"links":{"cited_paper":"/paper/2406.01394","citing_paper":"/paper/2508.09194"},"observation_digest":"sha256:0508864babc922ecbb8e2ba441a52769d7effb17a6360d62cf981efe8f1b0966","observation_id":"98ce9784-1589-461b-bcba-a66cb3431239","resolution":{"observed_at":"2026-08-05T22:58:28.517009Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01394","last_updated":"2025-05-28T12:38:37Z","snapshot_observed_at":"2026-07-06T18:24:30.706727Z","submitted_at":"2024-06-03T14:57:39Z","title":"PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration","version":5},"cited_work":{"arxiv_id":"2406.01394","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.01394","snapshot_observed_at":"2026-07-03T01:27:31.548927Z","title":"arXiv preprint arXiv:2406.01394 , year=","venue":null,"work_id":"158ec4a8-3254-4b08-8a08-a747245cb98a","year":null},"citing_paper":{"arxiv_id":"2606.09132","last_updated":"2026-06-08T07:30:20Z","snapshot_observed_at":"2026-08-05T18:32:48.128378Z","submitted_at":"2026-06-08T07:30:20Z","title":"Vision Language Model Helps Private Information De-Identification in Vision Data","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-06-27T16:29:33.294960Z"},"links":{"cited_paper":"/paper/2406.01394","citing_paper":"/paper/2606.09132"},"observation_digest":"sha256:494707c3ee1712a04880dc4d309e663b6c987cc556306c2eb5638b35a8b63ea1","observation_id":"cb5d5872-3341-44ec-802d-cf3855a5ee1a","resolution":{"observed_at":"2026-07-03T01:27:31.550204Z","resolver_source":"arxiv_id","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"}}],"links":{"evidence":"/evidence","html":"/paper/2406.01394/citation-record","integrity":"/paper/2406.01394/integrity","json":"/paper/2406.01394/citation-record.json","paper":"/paper/2406.01394"},"outbound":[],"paper":{"arxiv_id":"2406.01394","last_updated":"2025-05-28T12:38:37Z","latest_version":5,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T18:24:30.706727Z","submitted_at":"2024-06-03T14:57:39Z","title":"PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration"},"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":"2026-08-07T06:34:17.273281+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 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.01394."}