{"as_of":"2026-08-08T01:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b834180883824a76ee2c3fe77504061c8d842806605786c3c30900f5d9a9101a","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T13:19:11.815903Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-21T08:32:32.410473Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T08:34:05.462671Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"cited_work":{"arxiv_id":"2509.00772","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.00772","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"61962aa4-869b-4746-9b24-17cfc006a4e5","year":null},"citing_paper":{"arxiv_id":"2605.20248","last_updated":"2026-05-18T06:47:41Z","snapshot_observed_at":"2026-07-06T23:30:53.900592Z","submitted_at":"2026-05-18T06:47:41Z","title":"Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-21T08:32:32.410473Z"},"links":{"cited_paper":"/paper/2509.00772","citing_paper":"/paper/2605.20248"},"observation_digest":"sha256:02d821743bb2a69583af7d73ef2da09251ced3a00ca1571d5d2771fe97c59be3","observation_id":"4e635ee6-a430-406d-8c59-bcdc5b574f11","resolution":{"observed_at":"2026-05-21T08:34:05.464423Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2509.00772/citation-record","integrity":"/paper/2509.00772/integrity","json":"/paper/2509.00772/citation-record.json","paper":"/paper/2509.00772"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2006.07988","last_updated":"2021-10-26T20:07:59Z","snapshot_observed_at":"2026-07-06T09:28:59.431672Z","submitted_at":"2020-06-14T19:27:39Z","title":"Adaptive Universal Generalized PageRank Graph Neural Network","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.07988","snapshot_observed_at":"2026-08-05T13:19:10.015533Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.015533Z"},"links":{"cited_paper":"/paper/2006.07988","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:65a4bbd5107767c1f39669a140d9747504e74b1f61efcb058cf1b5fd4552e1ab","observation_id":"f8d9307d-4fbb-4ac0-a4dd-20bc686b3987","resolution":{"observed_at":"2026-08-05T13:19:10.015533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05718","last_updated":"2020-12-31T08:23:06Z","snapshot_observed_at":"2026-08-06T17:19:10.018602Z","submitted_at":"2020-04-12T23:30:00Z","title":"Principal Neighbourhood Aggregation for Graph Nets","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.05718","snapshot_observed_at":"2026-08-05T13:19:10.055306Z","title":"2020.PrincipalNeighbourhoodAggregationforGraphNets","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.055306Z"},"links":{"cited_paper":"/paper/2004.05718","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:37628fb24af2d586d5ca61a8b85a8bdf42a967f4b7e86ce91d0e8a3549d245ab","observation_id":"979aad24-9dc2-408a-80af-742d5693c4bb","resolution":{"observed_at":"2026-08-05T13:19:10.055306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.01232","last_updated":"2024-04-06T23:26:26Z","snapshot_observed_at":"2026-07-06T17:38:34.497555Z","submitted_at":"2024-03-02T15:32:01Z","title":"Polynormer: Polynomial-Expressive Graph Transformer in Linear Time","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.01232","snapshot_observed_at":"2026-08-05T13:19:10.132238Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.132238Z"},"links":{"cited_paper":"/paper/2403.01232","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:6b48813ca9669586489d5625801791b49ae9ebd4fe86e9f410bbd552745ccef4","observation_id":"f7682c4c-e3f5-43aa-bf60-45175b241504","resolution":{"observed_at":"2026-08-05T13:19:10.132238Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1704.01212","last_updated":"2017-06-12T20:52:56Z","snapshot_observed_at":"2026-08-07T07:38:05.448298Z","submitted_at":"2017-04-04T23:00:44Z","title":"Neural Message Passing for Quantum Chemistry","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.01212","snapshot_observed_at":"2026-08-05T13:19:10.243000Z","title":"Schoenholz, Patrick F","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.243000Z"},"links":{"cited_paper":"/paper/1704.01212","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:9715d63861c296961981aed8080f3fef77c45c0ad01e168e328427a32a8a237d","observation_id":"93a78ab5-d828-444a-b789-fa0170ae10cb","resolution":{"observed_at":"2026-08-05T13:19:10.243000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.02216","last_updated":"2018-09-10T14:26:58Z","snapshot_observed_at":"2026-07-06T05:45:54.936325Z","submitted_at":"2017-06-07T14:51:05Z","title":"Inductive Representation Learning on Large Graphs","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.02216","snapshot_observed_at":"2026-08-05T13:19:10.359918Z","title":"InductiveRepresentation Learning on Large Graphs.CoRR abs/1706.02216 (2017)","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.359918Z"},"links":{"cited_paper":"/paper/1706.02216","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:cd0623c73acacc8f2743b229b9237f8053e10afae32a88d564baa4df2c4862a1","observation_id":"10fa268e-6b14-4358-8dcf-5818aecc64f5","resolution":{"observed_at":"2026-08-05T13:19:10.359918Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.11691","last_updated":"2022-10-20T06:37:38Z","snapshot_observed_at":"2026-08-07T06:28:35.011378Z","submitted_at":"2022-05-24T01:12:54Z","title":"High-Order Pooling for Graph Neural Networks with Tensor Decomposition","version":2},"cited_work":{"arxiv_id":"2205.11691","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.11691","snapshot_observed_at":"2026-08-05T13:19:12.776199Z","title":"High-Order Pooling for Graph Neural Networks with Tensor Decomposition","venue":"cs.LG","work_id":"12caa89f-1e63-4cd1-b520-ce896509b96d","year":2022},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.438743Z"},"links":{"cited_paper":"/paper/2205.11691","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:918fb4886df6b9a72bfa72ec267e717dab9114830edc3807db96c3aac4444658","observation_id":"551a4a4f-4d49-4daa-9af0-ee40c2305504","resolution":{"observed_at":"2026-08-05T13:19:12.852121Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-05T13:19:10.519166Z","title":"Kipf and Max Welling","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.519166Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:87ee4f8a1be1f008462fe093b596e0d0f7d672d5feb746eb7c156267b82a57de","observation_id":"3f28ce7f-07ea-4188-b8f9-fdd54f9e4c80","resolution":{"observed_at":"2026-08-05T13:19:10.519166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.07308","last_updated":"2022-05-15T15:24:26Z","snapshot_observed_at":"2026-07-06T13:10:06.071526Z","submitted_at":"2022-05-15T15:24:26Z","title":"Finding Global Homophily in Graph Neural Networks When Meeting Heterophily","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.07308","snapshot_observed_at":"2026-08-05T13:19:10.595554Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.595554Z"},"links":{"cited_paper":"/paper/2205.07308","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:611bb5ce53124a1fdd6b900ffed447ba68a16749e59f2940beb14b8c5e2e6397","observation_id":"c51567b6-f4e8-4370-ab6f-23ff40d48678","resolution":{"observed_at":"2026-08-05T13:19:10.595554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.05493","last_updated":"2017-09-22T21:36:00Z","snapshot_observed_at":"2026-07-06T04:36:48.493556Z","submitted_at":"2015-11-17T18:10:12Z","title":"Gated Graph Sequence Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.05493","snapshot_observed_at":"2026-08-05T13:19:10.671729Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.671729Z"},"links":{"cited_paper":"/paper/1511.05493","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:e45ef75988170d668dce9d54f4aaf1e46b95c4e21cf32c2cf2cada9615d32d5a","observation_id":"a67d44d9-5b69-4398-b064-e97f8e332adf","resolution":{"observed_at":"2026-08-05T13:19:10.671729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04738","last_updated":"2024-12-06T02:59:01Z","snapshot_observed_at":"2026-07-06T20:02:35.216265Z","submitted_at":"2024-12-06T02:59:01Z","title":"DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling","version":1},"cited_work":{"arxiv_id":"2412.04738","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04738","snapshot_observed_at":"2026-08-05T13:19:12.564474Z","title":"DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling","venue":"cs.LG","work_id":"412c2157-dd8e-4e50-a4f5-45a1f07d3f9b","year":2024},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.750859Z"},"links":{"cited_paper":"/paper/2412.04738","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:37a38dd034bb2abf514c4a7743403f4785ef447b511fdc8d2f1d34b38bf6657b","observation_id":"f194c9d0-a74c-4e43-b880-709d3641f23a","resolution":{"observed_at":"2026-08-05T13:19:12.642520Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.07634","last_updated":"2021-05-17T06:46:01Z","snapshot_observed_at":"2026-08-07T16:28:55.706918Z","submitted_at":"2021-05-17T06:46:01Z","title":"Improving Graph Neural Networks with Simple Architecture Design","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.07634","snapshot_observed_at":"2026-08-05T13:19:10.813138Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.813138Z"},"links":{"cited_paper":"/paper/2105.07634","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:f0c6d4f2616a7fdf06b3fc8d56b441e074610d2d5a0de595ad222e998ea8757e","observation_id":"9098da82-baf3-4620-a6cb-5b85a121a1d8","resolution":{"observed_at":"2026-08-05T13:19:10.813138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.11640","last_updated":"2024-03-02T21:17:13Z","snapshot_observed_at":"2026-08-06T06:30:03.262182Z","submitted_at":"2023-02-22T20:32:59Z","title":"A critical look at the evaluation of GNNs under heterophily: Are we really making progress?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.11640","snapshot_observed_at":"2026-08-05T13:19:10.866489Z","title":"AcriticallookattheevaluationofGNNsunderheterophily: Are we really making progress? arXiv:2302.11640 [cs.LG] https://arxiv.org/abs/ 2302.11640","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.866489Z"},"links":{"cited_paper":"/paper/2302.11640","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:33a56f0066dc43e14acff9a503ab17252ac30e2bd082738a38963a6f8a2a49ab","observation_id":"79625630-3a2f-415b-b8a7-20437397d768","resolution":{"observed_at":"2026-08-05T13:19:10.866489Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10498","last_updated":"2023-11-28T18:33:37Z","snapshot_observed_at":"2026-08-05T06:02:54.004996Z","submitted_at":"2023-05-17T18:06:43Z","title":"Edge Directionality Improves Learning on Heterophilic Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10498","snapshot_observed_at":"2026-08-05T13:19:10.948749Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:10.948749Z"},"links":{"cited_paper":"/paper/2305.10498","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:8beed86c06d03c1f3bc12eecfd58f8fa97f007058438287d59483df293230768","observation_id":"7f12add5-756f-4757-82f5-f0dcc288e398","resolution":{"observed_at":"2026-08-05T13:19:10.948749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.00513","last_updated":"2023-03-15T16:54:00Z","snapshot_observed_at":"2026-08-03T15:41:10.199638Z","submitted_at":"2022-10-02T13:19:48Z","title":"Gradient Gating for Deep Multi-Rate Learning on Graphs","version":2},"cited_work":{"arxiv_id":"2210.00513","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.00513","snapshot_observed_at":"2026-08-05T13:19:12.388427Z","title":"Gradient Gating for Deep Multi-Rate Learning on Graphs","venue":"cs.LG","work_id":"1169cefb-c166-4c43-9ece-f6b0d49dda9c","year":2022},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.020081Z"},"links":{"cited_paper":"/paper/2210.00513","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:8cbd5f0d44310e53776acf107a30b753e5fbc61d9c5f9d8b7f1db1acb6f14a0b","observation_id":"b0a6eb72-1b60-418f-8426-76b06140778d","resolution":{"observed_at":"2026-08-05T13:19:12.452536Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:19:11.094614Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.094614Z"},"links":{"citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:3c93dfeed9539816eb010c241351059bca132b75ab7f7a99cd8b380c3d1e5679","observation_id":"34b9edf3-ca05-474d-8bfb-2dc8d22b0b25","resolution":{"observed_at":"2026-08-05T13:19:11.094614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.01524","last_updated":"2023-02-03T03:38:50Z","snapshot_observed_at":"2026-07-06T14:47:56.365341Z","submitted_at":"2023-02-03T03:38:50Z","title":"Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.01524","snapshot_observed_at":"2026-08-05T13:19:11.186234Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.186234Z"},"links":{"cited_paper":"/paper/2302.01524","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:74e720fbb7202fecf6ebb6da2c8e190d725434a86234d488ee9c72d5f8cf5007","observation_id":"17a20ecd-9c25-40d5-ad92-f937928e71b9","resolution":{"observed_at":"2026-08-05T13:19:11.186234Z","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":"2026-08-05T13:19:12.997466Z","title":null,"venue":null,"work_id":"7b20c792-d514-4867-a1c1-5d02ab755106","year":2020},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.282112Z"},"links":{"citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:cc57ca58c8a5b3ef0285b90a2d8a49962da7b3ab7a1eb893519e5221d59e4135","observation_id":"f61ccd4f-6924-4e08-a25b-d1de4b7bc970","resolution":{"observed_at":"2026-08-05T13:19:13.083483Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.13970","last_updated":"2020-04-29T06:19:10Z","snapshot_observed_at":"2026-07-06T09:16:05.338672Z","submitted_at":"2020-04-29T06:19:10Z","title":"Directed Graph Convolutional Network","version":1},"cited_work":{"arxiv_id":"2004.13970","doi":null,"metadata_source":"pith","pith_arxiv_id":"2004.13970","snapshot_observed_at":"2026-08-05T13:19:12.138061Z","title":"Directed Graph Convolutional Network","venue":"cs.LG","work_id":"2d959f7c-5a0b-4dd7-9f1c-293198f2a3f3","year":2020},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.359682Z"},"links":{"cited_paper":"/paper/2004.13970","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:d8d27d7284b8182b369fa5e3bc4bf4a22416916ba4a9399a20f67a5ed8fa3599","observation_id":"d08870ec-52b5-43dd-a85a-8b7172a1a216","resolution":{"observed_at":"2026-08-05T13:19:12.201011Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10903","last_updated":"2018-02-04T19:13:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-10-30T12:41:12Z","title":"Graph Attention Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10903","snapshot_observed_at":"2026-08-05T13:19:11.411295Z","title":"GraphAttentionNetworks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.411295Z"},"links":{"cited_paper":"/paper/1710.10903","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:e2d15ede31dc7bcbc4cc6f3c730048bc61a4aeecc441297daf826e52e6984988","observation_id":"8da13e73-501d-4ff7-9a88-41ba16fb6b15","resolution":{"observed_at":"2026-08-05T13:19:11.411295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.00596","last_updated":"2019-12-04T01:43:00Z","snapshot_observed_at":"2026-08-07T13:22:06.360133Z","submitted_at":"2019-01-03T03:20:55Z","title":"A Comprehensive Survey on Graph Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.00596","snapshot_observed_at":"2026-08-05T13:19:11.499175Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.499175Z"},"links":{"cited_paper":"/paper/1901.00596","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:834043d46f15944a3950c6ceb507e9b8e9a30a599ca5051906577ad7fdfca9d3","observation_id":"bdebe5a9-343f-4b6c-a866-f98757f27a89","resolution":{"observed_at":"2026-08-05T13:19:11.499175Z","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":"2026-08-05T13:19:11.592755Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.592755Z"},"links":{"citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:c0c96bad899dfa1e1bf36eb0fc51ba01ffded5787f93d8b92df55f537f6aae72","observation_id":"aeacd075-9df1-4be6-b786-d9546bba34c4","resolution":{"observed_at":"2026-08-05T13:19:11.592755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.11391","last_updated":"2021-06-11T04:29:07Z","snapshot_observed_at":"2026-08-06T19:41:51.618858Z","submitted_at":"2021-02-22T22:40:57Z","title":"MagNet: A Neural Network for Directed Graphs","version":2},"cited_work":{"arxiv_id":"2102.11391","doi":null,"metadata_source":"pith","pith_arxiv_id":"2102.11391","snapshot_observed_at":"2026-08-05T13:19:11.920102Z","title":"MagNet: A Neural Network for Directed Graphs","venue":"cs.LG","work_id":"5d0e716b-0510-476a-833c-0d0086e5762f","year":2021},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.734050Z"},"links":{"cited_paper":"/paper/2102.11391","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:6bf88f44b21d87ce3dfa4d66fe726b7514bb178e17c98219f17987fd028de385","observation_id":"b2c3f277-601c-4cec-9622-67a6eb413f85","resolution":{"observed_at":"2026-08-05T13:19:12.015708Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.11468","last_updated":"2020-10-23T08:43:25Z","snapshot_observed_at":"2026-07-06T09:30:56.502340Z","submitted_at":"2020-06-20T02:05:01Z","title":"Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.11468","snapshot_observed_at":"2026-08-05T13:19:11.815903Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.815903Z"},"links":{"cited_paper":"/paper/2006.11468","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:09a87894047142f5fcd97c218a344c867bfec6e69054a3de70dafeb20992c8bd","observation_id":"76ac5007-9920-4d57-8231-f891eadbf68c","resolution":{"observed_at":"2026-08-05T13:19:11.815903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.06462","last_updated":"2022-11-28T16:08:41Z","snapshot_observed_at":"2026-08-06T13:29:28.071301Z","submitted_at":"2021-02-12T11:52:34Z","title":"Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.06462","snapshot_observed_at":"2026-08-05T13:19:11.672426Z","title":"arXiv:2102.06462 [cs.LG] https://arxiv.org/abs/ 2102.06462","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-05T13:19:11.672426Z"},"links":{"cited_paper":"/paper/2102.06462","citing_paper":"/paper/2509.00772"},"observation_digest":"sha256:616666049aeb0672d383de63ce549bec3311cea16989f176d01028373870b7e5","observation_id":"2e07ee51-5caf-41d3-85ba-3572be7e65fb","resolution":{"observed_at":"2026-08-05T13:19:11.672426Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.00772","last_updated":"2025-08-31T10:03:15Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T06:27:59.198185Z","submitted_at":"2025-08-31T10:03:15Z","title":"Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":19,"verified_exact":4,"verified_fuzzy":0},"total_outbound_references":24},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2509.00772."}