{"as_of":"2026-08-10T10:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d5261a44392fe23eb65e4ad3e9f6b3b65caa3a5f96c42c9131d86b2ca238e1a7","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T19:38:35.181978Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2502.00282/citation-record","integrity":"/paper/2502.00282/integrity","json":"/paper/2502.00282/citation-record.json","paper":"/paper/2502.00282"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:36.565463Z","title":"Slic superpixels compared to state-of-the-art superpixel methods","venue":null,"work_id":"12bd3f68-9170-40d5-951f-d0bb5e658e6a","year":2012},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.543974Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:940d83d315cbc962314de55d1774699c807f56e1219216ea168dea5fbc51212c","observation_id":"5224702c-2c23-4ae2-be7e-ebfcec72053c","resolution":{"observed_at":"2026-08-09T19:38:36.570055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2403.09898","last_updated":"2024-08-22T23:49:16Z","snapshot_observed_at":"2026-08-07T01:30:23.859437Z","submitted_at":"2024-03-14T22:19:37Z","title":"TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.09898","snapshot_observed_at":"2026-08-09T19:38:34.591847Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.591847Z"},"links":{"cited_paper":"/paper/2403.09898","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:0d29db7c3282cca28bcafeff63add8117c61e04e92036703edc2005eb253072e","observation_id":"5ec59e7f-f6d8-438c-bfd5-02c2d3a44fb3","resolution":{"observed_at":"2026-08-09T19:38:34.591847Z","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":"2026-08-09T19:38:36.551054Z","title":"Specformer: Spectral graph neural networks meet transformers","venue":null,"work_id":"7731dcc4-9065-4219-b606-fb3bf0fb1d11","year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.610998Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:ccdefe5a6ddcc82db2aa4628dc53bbca91ba66eabe0925d93cecbb0691a464c9","observation_id":"cb3dbbe5-470c-4c19-8970-f9e4ca04e53e","resolution":{"observed_at":"2026-08-09T19:38:36.555748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.616177Z","title":"and Elisseeff, A","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.616177Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:52b920f2647c7de2db09c7429487dcd0151ac4db0ab094ac6369ee908cd68538","observation_id":"b076cd49-6ada-47c2-952c-d426e102f6b6","resolution":{"observed_at":"2026-08-09T19:38:34.616177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.07553","last_updated":"2018-04-24T08:19:32Z","snapshot_observed_at":"2026-08-09T01:06:08.452911Z","submitted_at":"2017-11-20T21:28:40Z","title":"Residual Gated Graph ConvNets","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.07553","snapshot_observed_at":"2026-08-09T19:38:34.620516Z","title":"and Laurent, T","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.620516Z"},"links":{"cited_paper":"/paper/1711.07553","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:7e0ce426cea0c9fe590eef15430908278dcac59e6b2b5f46d66c0c9ad79ac6d9","observation_id":"80f96444-2932-4abc-a29f-d3ae82fbc563","resolution":{"observed_at":"2026-08-09T19:38:34.620516Z","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":"2026-08-09T19:38:36.527213Z","title":"I., Bronstein, M., Webb, S., and Rossi, E","venue":null,"work_id":"1591abf5-e55e-413a-8e16-35dd81fb5859","year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.626293Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:6ff1e20ac4b3c017977cb1ec14b51321bec1fce2fef33f6ec8cf3c6799d16dcd","observation_id":"3a0122e0-863e-4bb4-bc4b-944d4d722824","resolution":{"observed_at":"2026-08-09T19:38:36.531561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:36.512170Z","title":"Principal neighbourhood aggregation for graph nets","venue":null,"work_id":"8ef6105a-f0f0-4b13-90e6-d3b4f1c80508","year":2020},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.631635Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:86e2d31e420120845c3d87730685d47ee787ce15355258cff9cae1c230dc1548","observation_id":"ad4f1f92-69a7-4d1b-ab22-61e6a6811218","resolution":{"observed_at":"2026-08-09T19:38:36.517065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:36.497536Z","title":"Recurrent distance filtering for graph representation learning","venue":null,"work_id":"0cd1fc9a-1242-4c39-a8ac-6414a42927b3","year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.636353Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:b46dd6a84cf5175e10969e5d8c1909fa3c319ba2a1f84d88cebde2f6bc72b297","observation_id":"c5164edf-78f3-4248-8aa7-6aa38c838d85","resolution":{"observed_at":"2026-08-09T19:38:36.502449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.640372Z","title":"S., Hou, K., Salakhutdinov, R","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.640372Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:ebca882a94728866972d520599548677811d657a7fba07dec8830593c40b6b47","observation_id":"f308f6c6-0099-4661-a8fe-95ce954492a5","resolution":{"observed_at":"2026-08-09T19:38:34.640372Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.644865Z","title":"P., Ramp \\'a s ek, L., Galkin, M., Parviz, A., Wolf, G., Luu, A","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.644865Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:48a5cf71f3abf13f5b840484a9b991ea647c1c681c79738093135d56f0173acd","observation_id":"f6d0180e-e127-4763-994f-af1a44dac4ee","resolution":{"observed_at":"2026-08-09T19:38:34.644865Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.649050Z","title":"P., Joshi, C","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.649050Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:72a8ac9cbac955d9d5bd6e25c11800267553d92ad26359abb4b10a21cefb8d3b","observation_id":"7b877a88-f2ef-4b10-99c5-ae6b1412935a","resolution":{"observed_at":"2026-08-09T19:38:34.649050Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.653727Z","title":"K., Winn, J., and Zisserman, A","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.653727Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:29f646458077890396033d6f1b3151d78cc345b3f04f13545ad3ad083a2adf76","observation_id":"f5131161-01fe-4737-92c8-2e869770f8fe","resolution":{"observed_at":"2026-08-09T19:38:34.653727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01201","last_updated":"2024-11-28T07:10:33Z","snapshot_observed_at":"2026-08-10T10:16:07.821263Z","submitted_at":"2024-10-02T03:06:49Z","title":"Were RNNs All We Needed?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01201","snapshot_observed_at":"2026-08-09T19:38:34.658374Z","title":"O., Bengio, Y., and Hajimirsadegh, H","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.658374Z"},"links":{"cited_paper":"/paper/2410.01201","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:31ac916f377e090ca3f2063b1e5d9c6a8b4b40887c0598e01adb5131172de34f","observation_id":"6caa69af-69e0-4106-be57-7f82f8ad36b6","resolution":{"observed_at":"2026-08-09T19:38:34.658374Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.662833Z","title":"and Lenssen, J","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.662833Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:5e60cee828300b2b518bdd485be1757c0eb49cb777918f591958316fb69820c8","observation_id":"8492b3d5-822c-4454-afa2-645294322dbb","resolution":{"observed_at":"2026-08-09T19:38:34.662833Z","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":"2026-08-09T19:38:36.436355Z","title":"Understanding and extending subgraph gnns by rethinking their symmetries","venue":null,"work_id":"ce632b99-5e9b-4f46-b0ad-339f14fb2c59","year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.666886Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:f3f26174c528d16b93d40e9e6d66e28d230fb9d822af3c714fd65249a5e42f42","observation_id":"00d87e49-ba64-469e-95c6-458fe61adf79","resolution":{"observed_at":"2026-08-09T19:38:36.441199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2011.07682","last_updated":"2021-11-07T01:48:30Z","snapshot_observed_at":"2026-08-08T11:20:12.373575Z","submitted_at":"2020-11-16T01:50:21Z","title":"A Large-Scale Database for Graph Representation Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.07682","snapshot_observed_at":"2026-08-09T19:38:34.671540Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.671540Z"},"links":{"cited_paper":"/paper/2011.07682","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:5b00368ce179a053d167f2f089ada008eec2527cb999702a03de0884e544cb43","observation_id":"09ddf80d-0821-4763-bc5e-80d73f0f483f","resolution":{"observed_at":"2026-08-09T19:38:34.671540Z","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":"2026-08-09T19:38:36.421189Z","title":"and Leskovec, J","venue":null,"work_id":"ea46016f-f3ff-49b1-9aa4-eb1abe19abcf","year":2016},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.676666Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:5ad6ca1edc9f2de3e6422b19cde01a5414418bb75e924206d3c51f8ea30f2a57","observation_id":"29941c40-4234-4855-9ca5-c746e0330878","resolution":{"observed_at":"2026-08-09T19:38:36.426057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-09T19:38:34.681219Z","title":"and Dao, T","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.681219Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:d9505180c004828b49ef1a1bcccf5173fcbaaef83329ebb8f27091fb3870df86","observation_id":"ee806a95-c7c3-44fc-a2c4-024b88061548","resolution":{"observed_at":"2026-08-09T19:38:34.681219Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.685695Z","title":"Hippo: Recurrent memory with optimal polynomial projections","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.685695Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:cb269c32e409dc3bf6a65a77916fe61c779fdbeae85b423b5987fce8456b575d","observation_id":"1132c789-295a-4d25-b783-e3c016569d5e","resolution":{"observed_at":"2026-08-09T19:38:34.685695Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.690667Z","title":"Combining recurrent, convolutional, and continuous-time models with linear state space layers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.690667Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:14e8de58973fce3a8fec12331867a39b47cc3bf38b5a945cccc1a706b6c789a9","observation_id":"34f4bd45-6d1d-48a4-803a-9850d58928d6","resolution":{"observed_at":"2026-08-09T19:38:34.690667Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.695494Z","title":"Inductive representation learning on large graphs","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.695494Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:8245a45a37f68bc6f78a2e3ce5319fe27eeb31fb6f62cfc7b29688b64a45c31c","observation_id":"c6405df3-5678-4eef-b471-92131b28ccb3","resolution":{"observed_at":"2026-08-09T19:38:34.695494Z","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":"2026-08-09T19:38:36.376297Z","title":"Open graph benchmark: Datasets for machine learning on graphs","venue":null,"work_id":"87fc5232-5f04-4656-bfe7-d6d15c65d6be","year":2020},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.700290Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:9d8919de1b9875b84d77fdee9e6b3733f37f25d86167068db017cb7f54440fc0","observation_id":"3de6e515-83ad-4512-af7f-95dc08d13dad","resolution":{"observed_at":"2026-08-09T19:38:36.381285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:36.347680Z","title":"Boosting the cycle counting power of graph neural networks with i ^ 2 -gnns","venue":null,"work_id":"7feff1ab-cd5a-49ab-b904-97ec9c37a535","year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.704989Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:29db3388134d9347fc0c03e3d0a6c2dca0165f2a2055faae6bb340df023281af","observation_id":"5bdfb3df-a776-4b02-9065-4cc76ac5e12f","resolution":{"observed_at":"2026-08-09T19:38:36.365366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2310.02579","last_updated":"2024-06-08T16:09:55Z","snapshot_observed_at":"2026-08-09T19:51:55.168204Z","submitted_at":"2023-10-04T04:48:55Z","title":"On the Stability of Expressive Positional Encodings for Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02579","snapshot_observed_at":"2026-08-09T19:38:34.709534Z","title":"On the stability of expressive positional encodings for graph neural networks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.709534Z"},"links":{"cited_paper":"/paper/2310.02579","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:1dfc50b81f355c8d078407fb1c21ee1af8ae0f07df3b31a1a9cc73f9d0c6a3bc","observation_id":"a1d934d9-a9c2-4ab1-871a-9330446539ed","resolution":{"observed_at":"2026-08-09T19:38:34.709534Z","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":"2026-08-09T19:38:36.205310Z","title":"On the stability of expressive positional encodings for graph neural networks","venue":null,"work_id":"5b5d4dbe-618b-47f1-ad0f-7f072180b253","year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.714231Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:938937303499c1e4ca8313f44c4fd7cf774fa654038e9936a3e792713d51bced","observation_id":"fe7c2248-9a0f-4e79-a8d3-9298563f371b","resolution":{"observed_at":"2026-08-09T19:38:36.296711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2406.05815","last_updated":"2024-10-04T08:46:03Z","snapshot_observed_at":"2026-07-06T18:27:45.631190Z","submitted_at":"2024-06-09T15:03:36Z","title":"What Can We Learn from State Space Models for Machine Learning on Graphs?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.05815","snapshot_observed_at":"2026-08-09T19:38:34.718507Z","title":"What can we learn from state space models for machine learning on graphs? arXiv preprint arXiv:2406.05815, 2024 b","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.718507Z"},"links":{"cited_paper":"/paper/2406.05815","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:8cc04078d8241b5c3aa84b70b4af99f8be1ad0da43d1e8f9456afb41d2d15365","observation_id":"e26d119e-e931-43d3-be3d-63a916e09340","resolution":{"observed_at":"2026-08-09T19:38:34.718507Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.736186Z","title":"Neural tangent kernel: Convergence and generalization in neural networks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.736186Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:2e72a61fd1d9edf48ef60c393c2e9e8e1af0659a209e21ee3731f666334e90c8","observation_id":"19a40e2f-c3dd-43ba-be55-ca57cb574aa4","resolution":{"observed_at":"2026-08-09T19:38:34.736186Z","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":"2026-08-09T19:38:36.073740Z","title":"R., Savarese, S., and Saxena, A","venue":null,"work_id":"23eb4991-f5d6-428c-85d5-3bdd1bb30df5","year":2016},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.764246Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:5f2ae6afd5ed66040c4fd9e53a0c4dddf039a337a0b9dbf000d442a3deded425","observation_id":"25589607-dc2e-4168-ab18-b5bf00bf0072","resolution":{"observed_at":"2026-08-09T19:38:36.125462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.956091Z","title":null,"venue":null,"work_id":"6a0c7476-fd48-4f23-9543-b514d2e5fa33","year":2016},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.817103Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:679a961d214d156e3d14bfaf184b0e7d545533544a2fbf3bf0dd87458b96847d","observation_id":"4c06707b-3c1b-4db2-9655-59c72b8a7ab4","resolution":{"observed_at":"2026-08-09T19:38:36.009638Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:34.904145Z","title":"Rethinking graph transformers with spectral attention","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.904145Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:e7ce737b0efdc13b473bcd7e2f0e0f1d52b03bbb61f1d9ab7cf99e95cbbff520","observation_id":"40d3575d-5a98-40c7-b4b6-3d376e75231a","resolution":{"observed_at":"2026-08-09T19:38:34.904145Z","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":"2026-08-09T19:38:35.859513Z","title":"Distance encoding: Design provably more powerful neural networks for graph representation learning","venue":null,"work_id":"63a8c1a5-5cd4-49a9-a370-5165d34e5454","year":2020},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:34.947975Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:150350eecde01cb6bc98a92f759e7ea99bc4d9d758b9f599ff55023f33b8df80","observation_id":"25e41407-e2a0-4724-966f-dce99cd6be91","resolution":{"observed_at":"2026-08-09T19:38:35.864498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.843951Z","title":"D., Zhao, L., Smidt, T., Sra, S., Maron, H., and Jegelka, S","venue":null,"work_id":"bbbb9ac5-ba5a-48a7-8d2f-fcc360409b00","year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.025166Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:ca4620e9d5c9684f687f25398874b37c9f438500fcd8dbad044fc72108fd155b","observation_id":"c6d4ac16-a5d7-4453-a756-c2ec38a8a504","resolution":{"observed_at":"2026-08-09T19:38:35.849051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.074287Z","title":"K., Coates, M., Torr, P., and Lim, S.-N","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.074287Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:01e99ca70add10fb1db108732a7e7d64f58ee3468cfabd965a2f280cdce0dcfe","observation_id":"1e132fa1-47e7-48bd-a824-50f9bc552e19","resolution":{"observed_at":"2026-08-09T19:38:35.074287Z","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":"2026-08-09T19:38:35.817410Z","title":"L., Lenssen, J","venue":null,"work_id":"aab7cbb5-8927-43e2-8311-ba8e8adbc228","year":2019},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.079060Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:8fbe407ad4b8b775c8aab2d6b86cff6e8b3381f3507d3e05ab21c8c3f5bb778a","observation_id":"ec9f10a0-1155-4600-98fc-ec20f42d7c88","resolution":{"observed_at":"2026-08-09T19:38:35.822346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.083845Z","title":"Deepwalk: Online learning of social representations","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.083845Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:f3ec3a1f02bc1d268ec11af003516fce4ef14cec39be12cfb1c11941e812d3a7","observation_id":"558b77bf-a14f-4a1d-976f-772a102e399d","resolution":{"observed_at":"2026-08-09T19:38:35.083845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.07532","last_updated":"2021-06-22T07:40:01Z","snapshot_observed_at":"2026-08-08T07:19:01.554491Z","submitted_at":"2019-11-18T10:46:15Z","title":"Graph Neural Ordinary Differential Equations","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.07532","snapshot_observed_at":"2026-08-09T19:38:35.089319Z","title":"Graph neural ordinary differential equations","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.089319Z"},"links":{"cited_paper":"/paper/1911.07532","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:70b4535adcc3ff7793ae94df84169dfe3584a1ae6f893867042bc29b5ce54f21","observation_id":"4535db7b-eabe-4d9a-a412-35f992a45a38","resolution":{"observed_at":"2026-08-09T19:38:35.089319Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.094475Z","title":"P., Luu, A","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.094475Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:031b3fc5e551abd34128e5b6e1fe565b63bd29114267d9786ea148ddaa664d0a","observation_id":"a810ab61-0736-4ad1-95ed-73859286edbe","resolution":{"observed_at":"2026-08-09T19:38:35.094475Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.099401Z","title":"Learnability, stability and uniform convergence","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.099401Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:8d1e81979d624fc9e46169d5cc15c315dd0f310636102b9bd754d330907a322c","observation_id":"02aba8e6-3be1-481d-b25b-032f13006a0b","resolution":{"observed_at":"2026-08-09T19:38:35.099401Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.104796Z","title":"J., and Sinop, A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.104796Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:9336dbcd75f46034bfde1ada6ab39f84baacd5070e043b492f11ac50de49f30b","observation_id":"d447374a-0949-4f7a-80cf-16c8765abdec","resolution":{"observed_at":"2026-08-09T19:38:35.104796Z","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":"2026-08-09T19:38:35.764566Z","title":"K., Bhalla, S., Usmani, S","venue":null,"work_id":"6f857f97-4e86-47b9-b099-13fc460ecf39","year":2016},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.109448Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:d73cf2dca80060cb4098a17e30e150b888a58152b42758a6ab4594c9dcba43a3","observation_id":"2e793033-f628-49d9-ba5c-428e839a2298","resolution":{"observed_at":"2026-08-09T19:38:35.769556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.113841Z","title":"Graph attention networks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.113841Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:90f1007de1a174ec142dd597d81f5f1f517c6566e8a0adbe931590d84a456daa","observation_id":"9dc9d0f5-c7fb-4c4a-8116-62df76468ec1","resolution":{"observed_at":"2026-08-09T19:38:35.113841Z","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":"2026-08-09T19:38:35.739728Z","title":"Equivariant and stable positional encoding for more powerful graph neural networks","venue":null,"work_id":"6035446e-3b5e-4d59-aee5-e6934aa59ba7","year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.118542Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:12e21aba54f3dfd4c7523dab8163de5e79aec2273781489ef62b06a06e29340f","observation_id":"07a673f1-b276-4476-a9f9-2f951e69d937","resolution":{"observed_at":"2026-08-09T19:38:35.744546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2404.09516","last_updated":"2024-04-15T07:24:45Z","snapshot_observed_at":"2026-08-10T03:43:24.928430Z","submitted_at":"2024-04-15T07:24:45Z","title":"State Space Model for New-Generation Network Alternative to Transformers: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.09516","snapshot_observed_at":"2026-08-09T19:38:35.123394Z","title":"State space model for new-generation network alternative to transformers: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.123394Z"},"links":{"cited_paper":"/paper/2404.09516","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:993c58833bafa62b9519bc0499bfc32b7ffcde50207277bfce85a46af6274b8d","observation_id":"e8b2fd3d-3358-4d60-a33a-532da9c5d6ef","resolution":{"observed_at":"2026-08-09T19:38:35.123394Z","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":"2026-08-09T19:38:35.725104Z","title":"and Cheng, Q","venue":null,"work_id":"2bc177b8-bd6f-4314-aa5a-8d5ff17256d3","year":2022},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.128716Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:bd96c5baee4c039ff0b65316ea66f515a5e3532d6f5fd3af739a8424a1516a98","observation_id":"f0699482-01ad-42c0-9943-f4d4f62513a6","resolution":{"observed_at":"2026-08-09T19:38:35.729283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.133162Z","title":"N., Gomes, J., Geniesse, C., Pappu, A","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.133162Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:fc23109b8a2e859537cbc46244a590236ad2ccfb5c720f7cad25696744a447b5","observation_id":"3c4a7509-2223-48e2-8157-9d6e4bfbc5e1","resolution":{"observed_at":"2026-08-09T19:38:35.133162Z","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":"2026-08-09T19:38:35.700398Z","title":"Continuous graph neural networks","venue":null,"work_id":"b809c1e6-394d-4776-aacf-1c85d71b768c","year":2020},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.137526Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:82cb28a0730f62c3aadbd497334312ccf0c24a6ac2ea0336ed9adc6c69aaff09","observation_id":"946db2c9-c598-467d-a491-1ef499c40381","resolution":{"observed_at":"2026-08-09T19:38:35.705463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.684775Z","title":"How powerful are graph neural networks? In International Conference on Learning Representations, 2018","venue":null,"work_id":"e0d81b04-ed2a-4073-9d3f-70ef3b41e118","year":2018},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.142232Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:056445a27a41daf6967401396d52809c3562c7e302c4c81200d03d2db9746622","observation_id":"46d0c812-d0e9-464d-9d4a-0884d1d21d91","resolution":{"observed_at":"2026-08-09T19:38:35.689753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.147008Z","title":"Do transformers really perform badly for graph representation? Advances in neural information processing systems, 34: 0 28877--28888, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.147008Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:f74e879135055c2b37d28752a8eb2bc5877cb376c3a6f7517dbe179a98a2d7df","observation_id":"ad53aeaf-36ef-4ade-bc92-57fb8a1e5a9b","resolution":{"observed_at":"2026-08-09T19:38:35.147008Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.150989Z","title":"Hierarchical graph representation learning with differentiable pooling","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.150989Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:cc2afdd6983cd43826b6366467ced04a8496bd2265a4269a3d0071e4019edaf9","observation_id":"c5f247a2-1687-497f-a37c-ec97e1d50e85","resolution":{"observed_at":"2026-08-09T19:38:35.150989Z","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":"2026-08-09T19:38:35.652958Z","title":"Position-aware graph neural networks","venue":null,"work_id":"9928735e-8de0-4ff4-be80-8b240844c49d","year":2019},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.155283Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:510f1c11eb8694b84af5957eb0db4179d052c6745bb295ab739d41ea5b9c6065","observation_id":"810b0ed5-2ff9-46f3-8cea-0e13107275fe","resolution":{"observed_at":"2026-08-09T19:38:35.656881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.638286Z","title":"M., Ying, R., and Leskovec, J","venue":null,"work_id":"76546aaf-09d5-42b0-81bf-ad1896257e44","year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.159623Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:567292f07982535d99d4bfe2456ddcd81e508b8c6d311360a2d2fd43d8fbdf10","observation_id":"a4d3faea-d759-44ed-b2cc-afe4afa0907d","resolution":{"observed_at":"2026-08-09T19:38:35.643034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2406.04336","last_updated":"2024-06-06T17:59:41Z","snapshot_observed_at":"2026-07-06T18:26:42.010940Z","submitted_at":"2024-06-06T17:59:41Z","title":"On the Expressive Power of Spectral Invariant Graph Neural Networks","version":1},"cited_work":{"arxiv_id":"2406.04336","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.04336","snapshot_observed_at":"2026-08-09T19:38:35.220147Z","title":"On the Expressive Power of Spectral Invariant Graph Neural Networks","venue":"cs.LG","work_id":"2fdd63cc-813d-47e2-aba0-78a667e73840","year":2024},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.164161Z"},"links":{"cited_paper":"/paper/2406.04336","citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:a3b0e222e351944538519b54d9cf95e05dcee065747f930ae00baecf2edddeee","observation_id":"f37b82d1-dc77-4328-b011-27d2ae97291b","resolution":{"observed_at":"2026-08-09T19:38:35.242346Z","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.168559Z","title":"and Li, P","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.168559Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:e6efa5182a776672893b0f93f890c12b7062f74c9dbab76ce50fc9e7492a892d","observation_id":"635435db-7aee-4d0c-8e97-baa40948e770","resolution":{"observed_at":"2026-08-09T19:38:35.168559Z","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":"2026-08-09T19:38:35.563829Z","title":"From stars to subgraphs: Uplifting any gnn with local structure awareness","venue":null,"work_id":"a48fbb3a-4dde-45fa-ab17-8bcae301c5ba","year":2021},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.172973Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:3c0df58b30e4f430384ba93dd62e42fa3bd9e9de23c51be3a7bb4d5266e7c581","observation_id":"4188e2c5-8b82-4b30-aa28-b7508352dc3a","resolution":{"observed_at":"2026-08-09T19:38:35.595519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.474760Z","title":"C., and Dong, X","venue":null,"work_id":"8084285f-5c8c-436c-9a6d-c6e4c96ffa02","year":2023},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.177461Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:26c63ab71f006145253ae25efd740772322c5f0c8cc27ddef77a5e0da8f69a9d","observation_id":"582bb691-8d13-4e67-9d5c-160e70cbe3af","resolution":{"observed_at":"2026-08-09T19:38:35.490524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T19:38:35.181978Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-09T19:38:35.181978Z"},"links":{"citing_paper":"/paper/2502.00282"},"observation_digest":"sha256:508c5e1bd283d2f6498f34a2f89d4bdb6601a113896713cd4ae497d3193460fc","observation_id":"5b7fac19-2dd8-4dfe-84f8-38ec27e57171","resolution":{"observed_at":"2026-08-09T19:38:35.181978Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.00282","last_updated":"2025-02-01T02:46:48Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T04:56:37.823825Z","submitted_at":"2025-02-01T02:46:48Z","title":"GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":32,"verified_exact":1,"verified_fuzzy":23},"total_outbound_references":56},"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 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2502.00282."}