{"as_of":"2026-08-10T04:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:da7d05e11da7f052e3c236d2778026712884ce83acdadd40a8806ad456833bb7","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":"2026-08-09T06:31:02.800959+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":"2026-08-06T19:28:20.653361Z","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":"2026-05-23T06:35:28.002346Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":"1906.04214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Topology attack and defense for graph neural networks: An optimization perspective","venue":null,"work_id":"f2652a19-c122-4cd7-bca3-54161572807a","year":1906},"citing_paper":{"arxiv_id":"2412.14738","last_updated":"2026-05-20T12:36:58Z","snapshot_observed_at":"2026-08-08T01:22:26.084751Z","submitted_at":"2024-12-19T11:10:48Z","title":"Spectrally unstable nodes drive reliability failures in graph learning","version":13},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-23T06:34:06.469336Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2412.14738"},"observation_digest":"sha256:cb428b78307d7827636b7ffe4e89ff6bf00d20043236ab198b395aa4400d0eb1","observation_id":"aaf6e258-a4ca-4ae3-b8ba-e96775cb54e2","resolution":{"observed_at":"2026-05-23T06:35:28.006837Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-08-06T19:28:20.653361Z","title":"Topology attack and defense for graph neural networks: An optimization perspective","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2507.05540","last_updated":"2025-07-07T23:43:24Z","snapshot_observed_at":"2026-08-07T03:05:14.952205Z","submitted_at":"2025-07-07T23:43:24Z","title":"Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:28:20.653361Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2507.05540"},"observation_digest":"sha256:f816bb2ad73d28f2a064349cef627071ce2193a0ac4b915ff894f47040bff534","observation_id":"f954aa37-de91-4e9d-af3d-38be6d007e47","resolution":{"observed_at":"2026-08-06T19:28:20.653361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-08-06T18:30:54.692882Z","title":"Topology attack and defense for graph neural networks: An optimization perspective.arXiv preprint arXiv:1906.04214,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2507.08212","last_updated":"2025-07-10T22:50:58Z","snapshot_observed_at":"2026-08-06T18:21:30.095416Z","submitted_at":"2025-07-10T22:50:58Z","title":"EvA: Evolutionary Attacks on Graphs","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-06T18:30:54.692882Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2507.08212"},"observation_digest":"sha256:7da3d151cce1e48a9ba11c17e4c7f91f79a22d5b0e684109f71671546cc5386d","observation_id":"4c95af20-b6b4-4b05-9ed6-f8ebdcc6f1f0","resolution":{"observed_at":"2026-08-06T18:30:54.692882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-08-05T13:44:10.181714Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.00387","last_updated":"2025-08-30T06:53:36Z","snapshot_observed_at":"2026-08-09T20:29:22.534930Z","submitted_at":"2025-08-30T06:53:36Z","title":"Unifying Adversarial Perturbation for Graph Neural Networks","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T13:44:10.181714Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2509.00387"},"observation_digest":"sha256:6c6c35da7f800c6ad61c939230639d21cde578feb4888f31158e81b140589fd4","observation_id":"5b1839a3-bb4a-4064-b1ca-abb005b6fb4e","resolution":{"observed_at":"2026-08-05T13:44:10.181714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":"1906.04214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Topology attack and defense for graph neural networks: An optimization perspective","venue":null,"work_id":"f2652a19-c122-4cd7-bca3-54161572807a","year":1906},"citing_paper":{"arxiv_id":"2512.08964","last_updated":"2026-05-15T15:13:23Z","snapshot_observed_at":"2026-08-03T04:39:06.010398Z","submitted_at":"2025-11-30T01:40:15Z","title":"T2T-LA: A Topology-to-Topology LLM Agent for Graph Learning with Neither Feature Access nor Task Knowledge","version":4},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-21T18:45:01.748067Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2512.08964"},"observation_digest":"sha256:740555e242af5694f06bc9e7be6296cc205a926e850295a6664f40bb80712001","observation_id":"13408b42-116d-4ef6-9c24-3c83a34a4be6","resolution":{"observed_at":"2026-05-21T18:45:28.806441Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":"1906.04214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Topology attack and defense for graph neural networks: An optimization perspective","venue":null,"work_id":"f2652a19-c122-4cd7-bca3-54161572807a","year":1906},"citing_paper":{"arxiv_id":"2604.15370","last_updated":"2026-04-15T09:02:23Z","snapshot_observed_at":"2026-08-03T00:27:14.837814Z","submitted_at":"2026-04-15T09:02:23Z","title":"TopFeaRe: Locating Critical State of Adversarial Resilience for Graphs Regarding Topology-Feature Entanglement","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T13:28:38.160625Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2604.15370"},"observation_digest":"sha256:03a8118caf61cec899ba5fcab8fd6f2196b373cc89ebf53c50abffdaf3345d3c","observation_id":"1efbaff2-7077-434c-b43a-ca66cf71b1b2","resolution":{"observed_at":"2026-05-10T13:30:26.668604Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.04214","snapshot_observed_at":"2026-08-01T15:05:33.879437Z","title":"Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI) , year =","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2607.18567","last_updated":"2026-07-20T23:03:26Z","snapshot_observed_at":"2026-08-08T16:17:43.321230Z","submitted_at":"2026-07-20T23:03:26Z","title":"Attacking Graph Foundation Models Through Their Shared Representation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-01T15:05:33.879437Z"},"links":{"cited_paper":"/paper/1906.04214","citing_paper":"/paper/2607.18567"},"observation_digest":"sha256:e0b6b7a2cd3a5bb2ac17611a4a3a5e594fdcd1ff1fab911b5aab17eeabd6404f","observation_id":"43f65323-492a-45ac-b03c-66fe7a477848","resolution":{"observed_at":"2026-08-01T15:05:33.879437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1906.04214/citation-record","integrity":"/paper/1906.04214/integrity","json":"/paper/1906.04214/citation-record.json","paper":"/paper/1906.04214"},"outbound":[],"paper":{"arxiv_id":"1906.04214","last_updated":"2019-10-14T22:09:35Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T07:59:19.943467Z","submitted_at":"2019-06-10T18:20:09Z","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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:1906.04214."}