{"as_of":"2026-08-11T01:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:480da58cd17a133c93a3205e634a2118bdceeea63cd29d2c8fa8b2e7167f8f9c","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T04:38:57.757369Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T19:46:59.976192Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.05384","last_updated":"2024-05-08T15:39:58Z","snapshot_observed_at":"2026-08-04T06:45:25.103619Z","submitted_at":"2023-08-10T07:02:24Z","title":"Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.05384","snapshot_observed_at":"2026-08-08T04:38:57.757369Z","title":"Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08576","last_updated":"2025-04-11T09:41:45Z","snapshot_observed_at":"2026-08-09T01:08:52.935162Z","submitted_at":"2025-02-12T17:10:34Z","title":"Mapping the Landscape of Generative AI in Network Monitoring and Management","version":2},"reference_index":180,"source":"pdf_text","source_observed_at":"2026-08-08T04:38:57.757369Z"},"links":{"cited_paper":"/paper/2308.05384","citing_paper":"/paper/2502.08576"},"observation_digest":"sha256:109dead792f0ae91d27ee17385f8e4674ae1a375bb86b31592217559d39cfc17","observation_id":"83134585-2c53-4662-a7a5-c82b518f11d3","resolution":{"observed_at":"2026-08-08T04:38:57.757369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.05384","last_updated":"2024-05-08T15:39:58Z","snapshot_observed_at":"2026-08-04T06:45:25.103619Z","submitted_at":"2023-08-10T07:02:24Z","title":"Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization","version":2},"cited_work":{"arxiv_id":"2308.05384","doi":null,"metadata_source":"pith","pith_arxiv_id":"2308.05384","snapshot_observed_at":"2026-08-06T19:46:59.976192Z","title":"Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization","venue":"cs.NI","work_id":"01f123ed-9bf1-4a11-b164-67c72e686605","year":2023},"citing_paper":{"arxiv_id":"2507.04807","last_updated":"2025-07-07T09:26:10Z","snapshot_observed_at":"2026-08-08T03:46:23.485663Z","submitted_at":"2025-07-07T09:26:10Z","title":"UAV-Assisted Integrated Communication and Over-the-Air Computation with Interference Awareness","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T19:46:59.206124Z"},"links":{"cited_paper":"/paper/2308.05384","citing_paper":"/paper/2507.04807"},"observation_digest":"sha256:1d94fe552664f3da0a6277b6d28f832ce37ca6e810928f8e4ec167d9a6a0f6a4","observation_id":"ec416bac-e160-4fe9-a305-17ed6267fc5f","resolution":{"observed_at":"2026-08-06T19:47:00.098588Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2308.05384/citation-record","integrity":"/paper/2308.05384/integrity","json":"/paper/2308.05384/citation-record.json","paper":"/paper/2308.05384"},"outbound":[],"paper":{"arxiv_id":"2308.05384","last_updated":"2024-05-08T15:39:58Z","latest_version":2,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-04T06:45:25.103619Z","submitted_at":"2023-08-10T07:02:24Z","title":"Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization"},"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 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.05384."}