{"as_of":"2026-08-20T07:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:59129ef404c6ffb5f4f5bd295ea3ebb5a3b52c9be1f18b1580c449ef6ee08e3d","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:53:27.147003Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2501.00595/citation-record","integrity":"/paper/2501.00595/integrity","json":"/paper/2501.00595/citation-record.json","paper":"/paper/2501.00595"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:28.563352Z","title":"Agarwal, H","venue":null,"work_id":"37d7c9fd-fb63-470e-9f30-d00a037dfbdf","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.471305Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:2f45d2c7a74e949a92e80a94aa2cdabc09566f0821af19c33ce31e166e73f158","observation_id":"dccbfa5d-1a6d-4309-bca8-458e3fc553d9","resolution":{"observed_at":"2026-08-10T22:53:28.567311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:26.548687Z","title":null,"venue":null,"work_id":null,"year":1982},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.548687Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:cce09aa52c996f63a0055f356042ee0dcf2dd6d80acd53711dd6795dfd5a5800","observation_id":"bdb3d6b2-3de0-4388-9ea0-98bffb8249d4","resolution":{"observed_at":"2026-08-10T22:53:26.548687Z","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":"2026-08-10T22:53:28.544417Z","title":null,"venue":null,"work_id":"32962fdb-bc7d-46d2-8744-4ae91b12f3b6","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.604345Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:addc93a8887fe4cf3a5c610458d3e4f3da1e190827d58e9e9c61a411476357c7","observation_id":"901e7451-e000-4142-b0d3-2d7da38affd2","resolution":{"observed_at":"2026-08-10T22:53:28.548334Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.00075","last_updated":"2017-07-07T01:31:36Z","snapshot_observed_at":"2026-08-18T22:23:56.302350Z","submitted_at":"2017-07-01T01:09:33Z","title":"Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.00075","snapshot_observed_at":"2026-08-10T22:53:26.655644Z","title":"Beutel, J","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.655644Z"},"links":{"cited_paper":"/paper/1707.00075","citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:7ab7fa5a7a2a679714e348c56a331c807e3f4e26a772be3e55759416965b4c4d","observation_id":"35a65bd6-baa8-4d28-a52e-ac9751914b95","resolution":{"observed_at":"2026-08-10T22:53:26.655644Z","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":"2026-08-10T22:53:28.532611Z","title":"Bose and W","venue":null,"work_id":"b625b981-a9bc-47d4-95e0-cdd0565a56d1","year":2019},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.693455Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:779c33e35ad0b5e4650bd1b8871d95042add630be252be3e5301ecf64e460469","observation_id":"ccf1acf7-99b8-46c6-ab4f-f24bbdef84fe","resolution":{"observed_at":"2026-08-10T22:53:28.536710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.05396","last_updated":"2024-02-21T22:25:01Z","snapshot_observed_at":"2026-08-18T19:47:45.911234Z","submitted_at":"2022-05-11T10:40:56Z","title":"A Survey on Fairness for Machine Learning on Graphs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.05396","snapshot_observed_at":"2026-08-10T22:53:26.699197Z","title":"Choudhary, C","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.699197Z"},"links":{"cited_paper":"/paper/2205.05396","citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:ac5350a421d737d9b3968807d8f3199387b57656f57f1627e3f504babdd48ab2","observation_id":"aeda93ea-2d2b-47c6-93c8-7273a123f3d4","resolution":{"observed_at":"2026-08-10T22:53:26.699197Z","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":"2026-08-10T22:53:28.521810Z","title":"Creager, D","venue":null,"work_id":"deee60e3-7f3b-47ac-b3a7-950e817c49ac","year":2019},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.704059Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:1328470e2aafe7b4142b4e840250aa1b5ae3dfd0d9ec4b420eb6ff340aaa2d40","observation_id":"8f9f378d-dc20-4772-8b96-f6ef145f89f5","resolution":{"observed_at":"2026-08-10T22:53:28.525202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.510748Z","title":"Dai and S","venue":null,"work_id":"3678195f-cbbe-42e1-9bc6-e61702be18a4","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.708045Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:f7efeb694dc6a7e6e5ba597fa52054680442004bad973f53402ad73cf726dbc2","observation_id":"66bdc2ac-573d-4d5a-9b3d-38196d4522c6","resolution":{"observed_at":"2026-08-10T22:53:28.514664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.499319Z","title":null,"venue":null,"work_id":"66b82c6a-e4af-428c-abb6-a06dada508f9","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.711941Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:e03a7871c6bbd27db8312f3eb38a3ef16b67ba6f36f37b24bd22fe8f17d116b8","observation_id":"f5173e34-15bc-4605-bc90-86316f8cc725","resolution":{"observed_at":"2026-08-10T22:53:28.503369Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.459455Z","title":null,"venue":null,"work_id":"1d8398ef-7667-4667-a16d-850342137b5f","year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.715831Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:1ae09a0b227560213038ebc3acbe70cc3352e1261b503eb0f47fd042fa88030c","observation_id":"015f0434-793f-42ad-91be-88bc2b3ffee4","resolution":{"observed_at":"2026-08-10T22:53:28.490892Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.332099Z","title":"Dwork, M","venue":null,"work_id":"20a022e6-39ed-4649-9a32-5d06ab4ef03d","year":2012},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.719702Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:38105f61db17f440e37fefd6b463f1e74326a89262a989776c2b494f23e826fa","observation_id":"a1e7305a-ea87-4604-adc4-9a4a69a93540","resolution":{"observed_at":"2026-08-10T22:53:28.370372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.319825Z","title":"Fisher, A","venue":null,"work_id":"3a7069d0-bcdc-4cd6-a562-477f742b958b","year":2020},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.724723Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:60807aea754ee862c0cae570f648c60f867fa5fa4d161727fcea7d1bd64220de","observation_id":"5289539c-36c9-4d38-866e-ef914d2264d0","resolution":{"observed_at":"2026-08-10T22:53:28.323920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.307418Z","title":"Grover and J","venue":null,"work_id":"27033684-ad47-404f-aab2-a6689a111bb4","year":2016},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.728948Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:19ec5311e560f4adf6d38d6d1c61475bd59fa4a2cdc3d05611de3b10439a82f4","observation_id":"d43d2d79-1665-4bb3-aabb-9af588e06523","resolution":{"observed_at":"2026-08-10T22:53:28.311447Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.295551Z","title":null,"venue":null,"work_id":"9160def9-c6ed-48c9-afc7-23a9ea71dea8","year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.732580Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:b6ea203574781ea5b118de5e70fd6a762eb95b8d919bbde07e08af6ce9495f51","observation_id":"121cd64a-f748-4d61-9c53-a9d10c3d36e6","resolution":{"observed_at":"2026-08-10T22:53:28.299567Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.283437Z","title":"Hardt, E","venue":null,"work_id":"555b171e-6847-4fc7-a439-cbd911c887b3","year":2016},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.737083Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:a6f17633e034ae43a4d2b2f976a59b2c47ff5d98349749d8bc0ba4a48df89639","observation_id":"334faf70-ac9f-4c41-82b4-6f07d5a49273","resolution":{"observed_at":"2026-08-10T22:53:28.287126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.270909Z","title":null,"venue":null,"work_id":"123cb9b7-afd0-494b-9860-5c15470b1955","year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.740944Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:99f59b0f09709226d590436fdcfd038367ebe1d088eb82beac1214110ee1a2af","observation_id":"ffc19ae8-59d8-4a4b-9af6-346068ce045f","resolution":{"observed_at":"2026-08-10T22:53:28.274904Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.258625Z","title":"Kamiran and T","venue":null,"work_id":"1f889720-41a3-4daa-8b8a-5c03e3d41b30","year":2012},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.744440Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:571100dac5a0e50bdb3e98c19758a8b9c0685d074ac7824b378149073e5e8ff7","observation_id":"980aef5c-4ee1-43e1-acb7-c7b5823f43ba","resolution":{"observed_at":"2026-08-10T22:53:28.262714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:26.748089Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.748089Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:2d7ce995320f1b980817f4ce6364423b0d31f1a001dfd00633fbc27d4cd26bc7","observation_id":"21ea678a-7904-461a-83a6-2b9273e1f8c5","resolution":{"observed_at":"2026-08-10T22:53:26.748089Z","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":"2026-08-10T22:53:28.237909Z","title":null,"venue":null,"work_id":"9f82203b-0aff-481f-8e83-937df6a0d1e3","year":1992},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.752216Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:c9fb323708cabdf6bf0abcf360325b84c5aa2a688ba21c6aa0d107fb61a5727a","observation_id":"35106381-7aaf-4629-8766-f3eaf4666ee1","resolution":{"observed_at":"2026-08-10T22:53:28.241949Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.226013Z","title":null,"venue":null,"work_id":"9c7cc68b-e7e0-4400-be3b-2f093fa5a935","year":2023},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.756163Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:e0e02e1b181c4a4e6f5bbb1f4aced3ae69b2b4b12b5ffad54d0333954641194d","observation_id":"e28e5493-da8c-49d4-8191-1cc9aa3731b7","resolution":{"observed_at":"2026-08-10T22:53:28.229752Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.08549","last_updated":"2022-01-21T05:49:15Z","snapshot_observed_at":"2026-08-16T17:26:56.346369Z","submitted_at":"2022-01-21T05:49:15Z","title":"Fair Node Representation Learning via Adaptive Data Augmentation","version":1},"cited_work":{"arxiv_id":"2201.08549","doi":null,"metadata_source":"pith","pith_arxiv_id":"2201.08549","snapshot_observed_at":"2026-08-10T22:53:27.192551Z","title":"Fair Node Representation Learning via Adaptive Data Augmentation","venue":"cs.LG","work_id":"8b556df2-9433-4f5d-b3f5-4596bc89015c","year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.760312Z"},"links":{"cited_paper":"/paper/2201.08549","citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:e74a00a94c1e0e5538fdde818a3c8524339de99b70febb4483638df2c877bd25","observation_id":"3fb5ec37-8fc0-4040-9e05-89dae682db82","resolution":{"observed_at":"2026-08-10T22:53:27.198845Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.214022Z","title":null,"venue":null,"work_id":"4a6f41a3-1063-4d72-a956-58f5f00475c4","year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.764507Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:3d9b6c13609b96112016997fa8c4c4a37a7f32e107055ffb46a7f294f7f8a770","observation_id":"919c8dd2-7b97-4da6-a812-0eabee028273","resolution":{"observed_at":"2026-08-10T22:53:28.218731Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:28.143103Z","title":null,"venue":null,"work_id":"a68ab5cb-70b2-4c04-a1a3-a49dd69a3e73","year":2023},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.767900Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:c67c316f900b77d4e9fee04cb3a9cf5ca40683aa4cbcec746978f36ed0585b99","observation_id":"c5fd1dbc-2017-4f40-888b-9e9542d98600","resolution":{"observed_at":"2026-08-10T22:53:28.206635Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.956031Z","title":"Mehrabi, F","venue":null,"work_id":"d508601b-167c-4b23-bc33-3ab8a29638d3","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.789428Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:73cfa41c8bb45f81f6225ae42d9f79b6754a28c2441e0e00f87c7cbaf16e4d9c","observation_id":"6951d371-649c-4fce-9aa4-cd5afb6c3e5c","resolution":{"observed_at":"2026-08-10T22:53:28.012689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.943892Z","title":null,"venue":null,"work_id":"b33ad433-93ce-43a8-b48f-8fe6f03611f0","year":1981},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.884353Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:5b3f3dcfbf44188765136080824aad51d635e9aa3947bc655f8be97ac20b16d2","observation_id":"d48e8bb6-eef7-4f63-87fc-a2e1c21097c1","resolution":{"observed_at":"2026-08-10T22:53:27.948086Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.931916Z","title":"Pleiss, M","venue":null,"work_id":"584a92e7-b5b7-4777-8635-873fbf07cca4","year":2017},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.955476Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:b6ae24c593a83da6fa5afeb4364b215dec8ba3faece86f2c963ad5781908dd2c","observation_id":"e142a3eb-5620-45d1-b758-8f1e814b38b6","resolution":{"observed_at":"2026-08-10T22:53:27.935774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.920673Z","title":"Rahman, B","venue":null,"work_id":"432d72c8-e370-4a84-8524-f0ddfb02ce1b","year":2019},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:26.986233Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:76450b6030561c2728e7a0e1ef89c561a874942e6c32c5dc2d01276eec9d82ba","observation_id":"5a5552b9-2189-4bdf-b9f7-b48051507daf","resolution":{"observed_at":"2026-08-10T22:53:27.924186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.908983Z","title":"Rajkomar, M","venue":null,"work_id":"4f391d2c-af91-4868-ac0f-934e0753ecbc","year":2018},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.067366Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:cb7975a299981f92796ef1e512915081bd2da305b024f3cc986464dc3aa73117","observation_id":"4090ef53-3027-4a53-8e76-40e388b62276","resolution":{"observed_at":"2026-08-10T22:53:27.912266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.896715Z","title":"Sharma, S","venue":null,"work_id":"0416ab98-9d1c-43a4-9e72-de600730bbb3","year":2023},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.107713Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:c348c7d4d67ac170a6f8f148278263c104ade380af4aee4280e128d223a98791","observation_id":"6df08c89-d54f-4f5e-84ca-435201bb35c8","resolution":{"observed_at":"2026-08-10T22:53:27.900978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.885456Z","title":null,"venue":null,"work_id":"56e03e4c-5150-47f6-9120-87a9a52ef58a","year":2020},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.111347Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:288908dfd120df34883df608597281d804954db08de593b390b3088e8b3e40ac","observation_id":"733eda4b-d3de-474a-9c40-99deb32defd1","resolution":{"observed_at":"2026-08-10T22:53:27.889431Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.858239Z","title":"Spinelli, S","venue":null,"work_id":"b79f3d4f-58e7-4201-80c7-af2659e84c3d","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.115122Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:3d8e19219ab3fd6ff8d51856e2ce538c241d1fd56e9cae88976086ac45534c04","observation_id":"3b4766eb-8617-484d-852b-b1b5d1cd5d89","resolution":{"observed_at":"2026-08-10T22:53:27.877789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.765041Z","title":"Takac and M","venue":null,"work_id":"baf0e1f0-18da-40fb-94f6-500fccd9ec9d","year":2012},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.118941Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:cd0411507a74922cc965185ae9e6f8d772ebbf0a81ac454fffadc10ce3112dbd","observation_id":"f3b2c79e-538f-4671-b942-1b7566f2fc73","resolution":{"observed_at":"2026-08-10T22:53:27.794496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.636101Z","title":"Vignac, I","venue":null,"work_id":"ebfb5f04-c842-4bb1-89d7-6323b4ddf723","year":2022},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.122790Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:f9c8570d17239509865db4a81fa58594f4d098d899f2e2a4d21a6f704f74d9d6","observation_id":"9bad4f9d-e470-4558-b22c-2d4a17b1e0bd","resolution":{"observed_at":"2026-08-10T22:53:27.721936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.505949Z","title":null,"venue":null,"work_id":"09fe1a5b-e7cd-4f5f-860d-c713597d04f0","year":2019},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.126700Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:524957db58cceb12f6f9c80f80b590415b0d7dee73b125337bf594b16c5b7e4d","observation_id":"167010f8-72dc-44a3-8d0a-c549a3017981","resolution":{"observed_at":"2026-08-10T22:53:27.569720Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.267725Z","title":"Xiong, Z","venue":null,"work_id":"dd311833-a28d-42a6-9eee-53b2f6be9ac1","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.129751Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:76c34c99c7658ec37104d067d389fbf6196d6c19f8c5395578942b580311b076","observation_id":"1b560a09-3a23-4983-b623-7b822b9136f0","resolution":{"observed_at":"2026-08-10T22:53:27.272088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.256138Z","title":null,"venue":null,"work_id":"60abcef2-f09d-421d-9865-c9bd098ac7e6","year":2017},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.133924Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:254a5cc909edb1e13bb19fd56a05c395c9ef131e26505ac3a6b320dea32ebaad","observation_id":"8e174245-9be0-4edc-9327-1e6d57eb43e3","resolution":{"observed_at":"2026-08-10T22:53:27.259695Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-10T22:53:27.244189Z","title":"Zemel, Y","venue":null,"work_id":"2d44b8a8-479e-4d7e-a25b-9bf4bfda3957","year":2013},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.138804Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:824ab06b2732424d592957d79e834ca40814887f275080d7ac3c3b1d0a274f90","observation_id":"70a16ff6-04f4-4472-b58c-51070c5b5c8c","resolution":{"observed_at":"2026-08-10T22:53:27.248202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.04131","last_updated":"2020-07-13T16:32:20Z","snapshot_observed_at":"2026-08-18T19:43:01.466508Z","submitted_at":"2020-06-07T11:50:45Z","title":"Deep Graph Contrastive Representation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.04131","snapshot_observed_at":"2026-08-10T22:53:27.142973Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.142973Z"},"links":{"cited_paper":"/paper/2006.04131","citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:ef0a4c51fea4a8d2fe070ddcc5491ee95735faf3bc757061840c50da3bc9ac6a","observation_id":"1f53e6be-152c-4c6c-9096-2e791a83793e","resolution":{"observed_at":"2026-08-10T22:53:27.142973Z","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":"2026-08-10T22:53:27.230947Z","title":null,"venue":null,"work_id":"64ba83ec-de25-47b9-be12-2fab7379f965","year":2021},"citing_paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:27.147003Z"},"links":{"citing_paper":"/paper/2501.00595"},"observation_digest":"sha256:9a67fa95d735de28f605bcde3a74a014859b7799e24046a50f0472074eeed2ee","observation_id":"c85911d3-9cdc-45a2-8c9f-51a6062164a6","resolution":{"observed_at":"2026-08-10T22:53:27.235867Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.00595","last_updated":"2024-12-31T18:48:30Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T19:47:32.679188Z","submitted_at":"2024-12-31T18:48:30Z","title":"Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":19},"total_outbound_references":39},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2501.00595."}