{"as_of":"2026-08-14T09:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:03475ee25123b1257ddc4ea06bc3e347af5ee1ce017a26610dc97db607175b34","coverage":[{"denominator":79,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":79,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T18:41:21.823852Z","state":"measured"},{"denominator":79,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":79,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2508.14338/citation-record","integrity":"/paper/2508.14338/integrity","json":"/paper/2508.14338/citation-record.json","paper":"/paper/2508.14338"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T18:41:34.992136Z","title":"A convergence analysis of gradient descent on graph neural networks","venue":null,"work_id":"25492f2c-01ba-4133-9b6c-52b2c1e3ca18","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:14.484549Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:0dfdb9f5f8fb526bdf7c058942a5914b824d432ac96389c140c16aa66a9531f7","observation_id":"877bfa7f-2429-488b-ab34-021d5341b98e","resolution":{"observed_at":"2026-08-05T18:41:35.104684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:34.659830Z","title":"and Moulines, E","venue":null,"work_id":"b5de8a22-311d-43bd-93bd-c3f305851c1d","year":2013},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:14.580166Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:746f9d8faea5eb1a7cbb7fa37479d3c5762dff6d4b971662476e23df58d6ca18","observation_id":"a385dfdf-efd8-4ffc-8ad8-6b1d615d9b14","resolution":{"observed_at":"2026-08-05T18:41:34.846326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.06966","last_updated":"2022-02-04T06:46:58Z","snapshot_observed_at":"2026-08-11T04:51:23.708275Z","submitted_at":"2021-02-13T17:46:57Z","title":"Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.06966","snapshot_observed_at":"2026-08-05T18:41:14.715907Z","title":"Graph convolution for semi-supervised classification: Improved linear separability and out-of-distribution generalization","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:14.715907Z"},"links":{"cited_paper":"/paper/2102.06966","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:e8961369e6e97d93925f6a90b5b6d2cd947993b590dac796243be58e30543b73","observation_id":"1230ade7-1b76-48ac-be07-9e5727a48f9f","resolution":{"observed_at":"2026-08-05T18:41:14.715907Z","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":"2026-08-05T18:41:34.358075Z","title":"L., Long, P","venue":null,"work_id":"80235076-b7a3-4e4c-8cfe-df16c5165c07","year":2020},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:14.876894Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:124ccee34684db7d5fc06acba772a7b6e17aeb4dd5ddeb4c765b9c9057dd07cf","observation_id":"fad8f795-04a9-402b-aadc-3782839576f7","resolution":{"observed_at":"2026-08-05T18:41:34.493383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:34.035056Z","title":"Tight nonparametric convergence rates for stochastic gradient descent under the noiseless linear model","venue":null,"work_id":"e8a61169-27e8-45d7-8c48-3174b8dce136","year":2020},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.032112Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:d8f7e28d06a460442a2330758cc666f1be5dc0ed1c18ffdf956a9d2fffa64a07","observation_id":"9ebb4865-9041-48f6-94fe-d1fb26f3b1cb","resolution":{"observed_at":"2026-08-05T18:41:34.175493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10568","last_updated":"2018-03-01T15:23:22Z","snapshot_observed_at":"2026-08-12T06:49:53.228636Z","submitted_at":"2017-10-29T06:14:00Z","title":"Stochastic Training of Graph Convolutional Networks with Variance Reduction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10568","snapshot_observed_at":"2026-08-05T18:41:15.153047Z","title":"Stochastic training of graph convolutional networks with variance reduction","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.153047Z"},"links":{"cited_paper":"/paper/1710.10568","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:ce9c3228321bc142a5e204b222097de937efb3039b07c258c957193136776a7f","observation_id":"04a591c0-3f7c-46f5-a2d2-17de600c2895","resolution":{"observed_at":"2026-08-05T18:41:15.153047Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.10247","last_updated":"2018-01-30T22:36:16Z","snapshot_observed_at":"2026-07-06T06:21:01.297755Z","submitted_at":"2018-01-30T22:36:16Z","title":"FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.10247","snapshot_observed_at":"2026-08-05T18:41:15.327172Z","title":"Fastgcn: fast learning with graph convolutional networks via importance sampling","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.327172Z"},"links":{"cited_paper":"/paper/1801.10247","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:1922f90772e699fafcd450a2ab7ff4765ddca3c3066d335f7409bed479827aeb","observation_id":"185c7349-b403-46bb-9a24-792aa7a59f05","resolution":{"observed_at":"2026-08-05T18:41:15.327172Z","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":"2026-08-05T18:41:33.758086Z","title":"Eigenvalues of random power law graphs","venue":null,"work_id":"17c00011-7ae2-4f73-931b-45d3f011c540","year":2003},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.497079Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:7c148a1bac3c6bdb79a7ca349aa2d82c01d84ce0f8a337324d9ca665b431fcf0","observation_id":"8b4a27b4-4404-4ef2-85c4-c78c9f682df3","resolution":{"observed_at":"2026-08-05T18:41:33.881089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:33.459512Z","title":null,"venue":null,"work_id":"c988c1c4-221c-42ae-896e-0f002582196c","year":1997},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.653112Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:f12798baf717a83710c0e238175d40cb4f33d7f085bfbfbb7e6d1687924d149a","observation_id":"66b655b4-dad6-4cdd-b998-4561a2d3022a","resolution":{"observed_at":"2026-08-05T18:41:33.615845Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:33.213478Z","title":"and Bach, F","venue":null,"work_id":"2684c882-5bd3-494a-b37f-0381bfab1f09","year":2015},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.818499Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:5916abd7b4597cbb716ef01cce1d01634144ea54bb95936364e9d91a77ef97ca","observation_id":"fab6d47b-5c5a-4623-8570-0f747887d238","resolution":{"observed_at":"2026-08-05T18:41:33.337574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:33.145169Z","title":"S., Foster, D","venue":null,"work_id":"a06bd9ce-6596-4e61-a5d4-544bb4def264","year":2013},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:15.944496Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:8c68e4fbd2f14d9b07ad196198a5ce16f46d37ff7a0882505d44b1be422fcda1","observation_id":"ec312054-a9b4-4af7-a8e4-abbbec563376","resolution":{"observed_at":"2026-08-05T18:41:33.201762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:32.930501Z","title":"Harder, better, faster, stronger convergence rates for least-squares regression","venue":null,"work_id":"e8286ffc-1f04-4154-97b5-c93d8ba22a27","year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.076181Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:f9dc178b33f3620ec16703cacce5fb40ebf2f2cd70f0c65ca674470bb279a769","observation_id":"427fd1b6-e7d5-4125-bbec-91691c6f32a3","resolution":{"observed_at":"2026-08-05T18:41:32.996006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:32.742945Z","title":"and Wager, S","venue":null,"work_id":"7e14b67a-9254-4817-847f-0c2c32c51ce1","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.165240Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:a4fa6bc12f88a6912eeb57acaec6ea58036f1c302d7a91cd8fdf69050538ca63","observation_id":"3767df2a-7e04-41c8-bb0b-165511b99872","resolution":{"observed_at":"2026-08-05T18:41:32.847541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:32.626819Z","title":"S., Hou, K., Salakhutdinov, R","venue":null,"work_id":"f8d64fde-d811-4747-a9e3-93c6a64f1fb6","year":2019},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.275227Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:1bd54ebf14021db5c4f7c4640f8d1a2e55f70d732904cca2973506b965729b63","observation_id":"c0410d9e-691a-4225-a9c2-0bdca5a659bf","resolution":{"observed_at":"2026-08-05T18:41:32.678288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:32.500253Z","title":"Networks, crowds, and markets, volume 8","venue":null,"work_id":"32bb18af-51e9-4954-9ab5-682bdd6cf250","year":2010},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.401466Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:65a8b1473794fe8c4d2ff94a3bbe6e3b617f1e465effb32c7e1ee1d6e0476589","observation_id":"8d2d2d94-0ab9-4e5d-92d9-ba027b1ceec4","resolution":{"observed_at":"2026-08-05T18:41:32.556885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:32.320431Z","title":"On power-law relationships of the internet topology","venue":null,"work_id":"b6e99270-437f-4e2f-9a68-d5be8ae58e0d","year":1999},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.499557Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:9c9554e5f8ffc2a5f8580c3122d6e33dfb8f8fb54942bd64b69fb89c49ea6b59","observation_id":"7d28f397-d68c-4c7b-893c-cfad77703a47","resolution":{"observed_at":"2026-08-05T18:41:32.411426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:32.137711Z","title":"real-world","venue":null,"work_id":"cf1d4b74-a052-4b51-886d-eb7048f732e9","year":2001},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.607280Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:24b9f5af6ebbddf83778f4bac69793f8bd58ba6d2d57aca9b676f23327b3b405","observation_id":"993218e3-1908-4187-b057-40f7c8665233","resolution":{"observed_at":"2026-08-05T18:41:32.230214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:31.938959Z","title":"Community detection in graphs","venue":null,"work_id":"6dfd24e2-b866-40f3-98a8-3f96fa3cbe63","year":2010},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.725554Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:884f12dec4da257725af989798a8e0d5fe0aaebceba3934a022b647b1a837d0c","observation_id":"519f79b1-154e-4030-ba11-a149788e31f6","resolution":{"observed_at":"2026-08-05T18:41:32.024617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:31.743228Z","title":"Identifying network structure similarity using spectral graph theory","venue":null,"work_id":"37ee6482-180d-4a8b-abb8-30e90171a196","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.813231Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:ceaf4c8a553e740db26030c3dbd44de8abe877b6ef4b9b97a09538fd8ee01640","observation_id":"7496bb54-4448-4540-b661-87ec1596dc5b","resolution":{"observed_at":"2026-08-05T18:41:31.823040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:31.544558Z","title":"S., Riley, P","venue":null,"work_id":"56232449-0e83-4992-b296-a92ccb0e3a49","year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:16.928402Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:0e1706607d14feb6a0b9cf80c9eafb59d1ec5a2c54a4a1280040b8dd5cbfac3d","observation_id":"1b9c71ff-4436-4677-94ad-5193bf4ec67d","resolution":{"observed_at":"2026-08-05T18:41:31.634581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:31.364356Z","title":"Spectra and eigenvectors of scale-free networks","venue":null,"work_id":"db80eefc-4215-44d3-a872-0cbac9f4fe83","year":2001},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.002739Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:1758fcd87cccb839aa36f6c259af42d7b7a5745a849d0681b3cb24ed55cb358e","observation_id":"00dc4c8f-6477-4824-8c8e-d21c23bb749d","resolution":{"observed_at":"2026-08-05T18:41:31.442505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:31.140725Z","title":"Exploring network structure, dynamics, and function using networkx","venue":null,"work_id":"89c5de93-d54a-47d3-bbd2-f6c75ddd536e","year":2008},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.084936Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:36774e7b42b780c16fe9378dc7e37d2e11605ef00a904a7db1519b193a01ebdc","observation_id":"643d31ff-8347-45fc-8115-ae545a20136e","resolution":{"observed_at":"2026-08-05T18:41:31.229132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:30.992961Z","title":"L., Ying, R., and Leskovec, J","venue":null,"work_id":"8c0c8570-9848-40f1-86a9-0141cd8ecc82","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.158408Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:63ab2b69654c7ade09dbb95a34fba8526ba26e16dc098748b94b37201ed3da15","observation_id":"8c3d9452-e8d4-44a4-b99e-04016d02f01f","resolution":{"observed_at":"2026-08-05T18:41:31.069487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:30.817087Z","title":"K., Vandergheynst, P., and Gribonval, R","venue":null,"work_id":"51405c96-44ff-45ce-8a4a-9050d72cc7e2","year":2011},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.223725Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:9e35f3087576da7ba58200969b10631129caad23f5454dbffb664d33384bee80","observation_id":"4f14e84d-4727-4ff2-8818-371c395cb739","resolution":{"observed_at":"2026-08-05T18:41:30.902648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:30.636051Z","title":"H., and Friedman, J","venue":null,"work_id":"0b2e67cf-eb8c-4399-8d89-3ac069629a09","year":2009},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.293573Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:fd5d1bc0147531b0ef6be1da936774c876a1a209bd78713b94aa54fc30c3c5d5","observation_id":"d17f3d1c-c098-4a89-8f06-f7db69f3b11a","resolution":{"observed_at":"2026-08-05T18:41:30.715641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:30.467318Z","title":null,"venue":null,"work_id":"b4d3d6a2-759a-4261-a0df-aafcd46ad107","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.367791Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:e1a13e21680835718756df513c374603065996c1ba666042fd517f59b7bbbb1b","observation_id":"a57af952-617a-46dd-87e8-f31f28558c09","resolution":{"observed_at":"2026-08-05T18:41:30.520034Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:30.311021Z","title":"M., and Zhang, T","venue":null,"work_id":"b74b092f-d041-4c14-88b9-b0de78283d07","year":2012},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.461093Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:7881815b127f400ce8fab40db9ac087816a2f6c4db1c530d52b434d07b1253f8","observation_id":"edfeec16-751e-45ed-9b98-f5fb2230a08f","resolution":{"observed_at":"2026-08-05T18:41:30.368430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.05343","last_updated":"2018-11-19T07:50:26Z","snapshot_observed_at":"2026-07-06T07:02:12.971488Z","submitted_at":"2018-09-14T10:33:27Z","title":"Adaptive Sampling Towards Fast Graph Representation Learning","version":3},"cited_work":{"arxiv_id":"1809.05343","doi":null,"metadata_source":"pith","pith_arxiv_id":"1809.05343","snapshot_observed_at":"2026-08-05T18:41:22.700431Z","title":"Adaptive Sampling Towards Fast Graph Representation Learning","venue":"cs.CV","work_id":"568ea2ee-41bb-429b-be06-c267213c432e","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.527494Z"},"links":{"cited_paper":"/paper/1809.05343","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:17614acc63f8ea54dddfb56a0413df8a6e132b8cebeab5b61bf15db7cfb6a27d","observation_id":"8940592f-9460-454e-ae3a-ce02a1ae50fa","resolution":{"observed_at":"2026-08-05T18:41:22.753927Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.09430","last_updated":"2018-07-21T21:13:33Z","snapshot_observed_at":"2026-07-06T06:06:06.859267Z","submitted_at":"2017-10-25T19:28:13Z","title":"A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares)","version":2},"cited_work":{"arxiv_id":"1710.09430","doi":null,"metadata_source":"pith","pith_arxiv_id":"1710.09430","snapshot_observed_at":"2026-08-05T18:41:22.504093Z","title":"A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares)","venue":"stat.ML","work_id":"4e06af59-8e74-48b4-b5f4-65b44361dadc","year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.589351Z"},"links":{"cited_paper":"/paper/1710.09430","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:0771e10d12adebadca72289a256cb09a9d61180669464eb34b89a6822219d3dc","observation_id":"adedd71d-8d4a-4fc1-af59-3aca0247fecb","resolution":{"observed_at":"2026-08-05T18:41:22.593576Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:30.128531Z","title":"M., Kidambi, R., Netrapalli, P., and Sidford, A","venue":null,"work_id":"c4daec72-31e8-4e92-b076-21827b36a139","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.657968Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:96d6a1a22d8930c323347b6ab2d927cc1b7996de8848b4a8aa1e882e152b4b3b","observation_id":"503d9771-b9ff-43f0-a68b-f4195f6b1a76","resolution":{"observed_at":"2026-08-05T18:41:30.206548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:29.919028Z","title":"Theory of graph neural networks: Representation and learning","venue":null,"work_id":"207ef7c0-87f9-45f4-a539-81b1174dd684","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.742469Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:5ad0b09e5122d4cde5d610683487a89e9b811b7d41a2db84b9bfc36baaa4010c","observation_id":"ac87c034-0f43-4ffa-8926-91fd71a43115","resolution":{"observed_at":"2026-08-05T18:41:30.010846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:29.741258Z","title":null,"venue":null,"work_id":"d4fccb70-b39a-4b69-bb0c-ac25d3bf3d3b","year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.857900Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:a1f1c9d512e970145e760155f80c646c9b5eafb569ade718660e3d83a39892a5","observation_id":"bb87baf8-05de-4594-8cf8-520e123c44e8","resolution":{"observed_at":"2026-08-05T18:41:29.824867Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:29.543768Z","title":"The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization","venue":null,"work_id":"1e909408-75bf-4071-afa9-67e75e2bcc16","year":2020},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:17.959454Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:3822aa3a0036a79887a72b5e52e22894adbef2716057ae68fcc388051fc46749","observation_id":"857e8ffe-e44e-46da-924b-44d7aed32880","resolution":{"observed_at":"2026-08-05T18:41:29.622755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:29.347112Z","title":"and Szepesvari, C","venue":null,"work_id":"a6b0a6df-de15-47d4-b897-abe4274cc5e4","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.044112Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:906ae3a1994dc39ee15096c5b6de0a1aad32fa5036794ebc8db7d11f30654948","observation_id":"69784b83-f544-4ab7-adff-ee2cdecf9ce5","resolution":{"observed_at":"2026-08-05T18:41:29.428686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:29.150171Z","title":"and Weisfeiler, B","venue":null,"work_id":"1f4a6430-9578-4823-80d2-a85da8a435d8","year":1968},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.129833Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:a75aa2c832c8be3bb6e8532af810a5c515c0e9f0d1fe8317358481c0ddf1f4d3","observation_id":"a3e4ed05-3cfe-46b8-a0a3-db283bfec3cd","resolution":{"observed_at":"2026-08-05T18:41:29.261948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:18.200964Z","title":"Deeper insights into graph convolutional networks for semi-supervised learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.200964Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:a6bdbdf1c98a64d429eb5d9346a0f06675281edc82bc0b85c2e73d469c77017b","observation_id":"ed4de45c-0723-47b6-9aca-89243fb68507","resolution":{"observed_at":"2026-08-05T18:41:18.200964Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.01926","last_updated":"2018-02-22T19:52:51Z","snapshot_observed_at":"2026-08-01T21:20:06.448984Z","submitted_at":"2017-07-06T18:20:59Z","title":"Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.01926","snapshot_observed_at":"2026-08-05T18:41:18.284884Z","title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.284884Z"},"links":{"cited_paper":"/paper/1707.01926","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:29e108f4a6a7b21af07797b0f370445efdbf1410925cf74b05beb59ddc7cdd53","observation_id":"94f5241d-fc8e-43d5-80a8-438de80f4c08","resolution":{"observed_at":"2026-08-05T18:41:18.284884Z","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":"2026-08-05T18:41:28.969575Z","title":"A \\ pac \\ -bayesian approach to generalization bounds for graph neural networks","venue":null,"work_id":"33293c6e-2236-4d97-a671-48ce3ca000b1","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.396213Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:16dbdecfe8ca1039509fa7adb858b383ddcca0b1176493c634ca9e348bc69600","observation_id":"4f85d4ec-24c3-45a8-aeec-871273e32d08","resolution":{"observed_at":"2026-08-05T18:41:29.036900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:28.808935Z","title":"Visual relationship detection with language priors, 2016","venue":null,"work_id":"1bd8681d-5ebb-4946-9868-949e3d390eb7","year":2016},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.473710Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:55036d13d68bd092135fd9adddf8321d5bcd3f41f78dd378b455387882e061ee","observation_id":"1f900806-9668-417d-8dfb-33350f12b598","resolution":{"observed_at":"2026-08-05T18:41:28.884647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:28.596468Z","title":"Generalization bounds for graph convolutional neural networks via rademacher complexity, 2021","venue":null,"work_id":"86d13170-345b-488c-aa4a-798a5281a7fc","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.620071Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:df29649552c86b4a7ee94b38ef98a3c95c36bf039db1baa4a438a3b1411202fb","observation_id":"e863b2b0-6751-4766-9df7-66d05d5e0930","resolution":{"observed_at":"2026-08-05T18:41:28.697034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.15535","last_updated":"2021-11-30T18:02:14Z","snapshot_observed_at":"2026-08-13T18:54:54.324752Z","submitted_at":"2021-06-29T16:13:41Z","title":"Subgroup Generalization and Fairness of Graph Neural Networks","version":2},"cited_work":{"arxiv_id":"2106.15535","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.15535","snapshot_observed_at":"2026-08-05T18:41:22.287356Z","title":"Subgroup Generalization and Fairness of Graph Neural Networks","venue":"cs.LG","work_id":"07d6b92b-e3d1-4dde-ac05-b92a70d9c1f2","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.717356Z"},"links":{"cited_paper":"/paper/2106.15535","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:0334e309a1c00e87a501a7d2d9a3e81482bd126ba8bc777f488fcbd6220e0c2a","observation_id":"af851030-7830-4616-a97e-535d040e0913","resolution":{"observed_at":"2026-08-05T18:41:22.380704Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:28.419868Z","title":"and Suzuki, T","venue":null,"work_id":"32ac3162-f620-4753-8fd7-c11ad400db61","year":2020},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.811017Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:b3dea85d10db30a6043983224b5ca257db1b8361c4004e4970f50e03c55c64a4","observation_id":"bbbbf1b5-ad54-4d81-8e08-b3454faff887","resolution":{"observed_at":"2026-08-05T18:41:28.491284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:28.265093Z","title":"Implicit regularization or implicit conditioning? exact risk trajectories of sgd in high dimensions","venue":null,"work_id":"9ba51b9b-84f5-4717-868b-029645b7eb15","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.913132Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:20f62afd764a6ae6c5c533f0a4530cd3589d732a2c7be75eb8d81e0ba2997803","observation_id":"e5653923-6cad-49e6-b744-aa156966ba53","resolution":{"observed_at":"2026-08-05T18:41:28.339596Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:28.094755Z","title":"and Barab \\'a si, A.-L","venue":null,"work_id":"ae2e03d6-d3de-4717-97c1-e81d61c6c750","year":2016},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:18.995987Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:5dbc8070e3a639bf5dbb87a1f93059ff80a8985e906a4b735c6e8758620a80b6","observation_id":"cb11845d-db09-4426-93d0-4461a75b07aa","resolution":{"observed_at":"2026-08-05T18:41:28.180450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:27.933243Z","title":"C., and Bonvin, A","venue":null,"work_id":"83911539-389b-4465-aea1-dd6441dedae3","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.100248Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:6380c7dbffa38e3f7461a6b4a78a5bd7f3dcd9d7a6128cebb2820dc88884458d","observation_id":"d3059129-63b7-48eb-8e69-cd77f6749606","resolution":{"observed_at":"2026-08-05T18:41:28.011195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:27.754327Z","title":"Graph neural networks for materials science and chemistry","venue":null,"work_id":"a5fe30f6-897a-4630-b51a-1cced4fd0bcf","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.239911Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:e83892165e70f4c05e78779889222867f605b833543f6aa0742881602b3191df","observation_id":"1176c815-9369-41d7-901c-7515f1f0d8ee","resolution":{"observed_at":"2026-08-05T18:41:27.845898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10993","last_updated":"2023-03-20T10:21:29Z","snapshot_observed_at":"2026-08-13T12:20:52.753435Z","submitted_at":"2023-03-20T10:21:29Z","title":"A Survey on Oversmoothing in Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10993","snapshot_observed_at":"2026-08-05T18:41:19.310455Z","title":"K., Bronstein, M","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.310455Z"},"links":{"cited_paper":"/paper/2303.10993","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:c612465468fe226b3be353900635ce6689194aa766d8a272278ebb1076e5f977","observation_id":"79923084-59cb-4ce2-85f7-723ec4572bd9","resolution":{"observed_at":"2026-08-05T18:41:19.310455Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.04078","last_updated":"2020-10-16T05:22:01Z","snapshot_observed_at":"2026-08-13T11:34:59.154854Z","submitted_at":"2020-03-09T12:37:40Z","title":"A Survey on The Expressive Power of Graph Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.04078","snapshot_observed_at":"2026-08-05T18:41:19.411539Z","title":"A survey on the expressive power of graph neural networks","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.411539Z"},"links":{"cited_paper":"/paper/2003.04078","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:351566e9f076a30af4fd40f84d5c501512353b1cc63dcb9c0a833e5a531882d7","observation_id":"aa344fdd-ff60-4d8d-bd08-31daf1898e43","resolution":{"observed_at":"2026-08-05T18:41:19.411539Z","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":"2026-08-05T18:41:27.540191Z","title":"C., and Hagenbuchner, M","venue":null,"work_id":"0973524c-d538-4cf3-b9c2-adb4ae1ecd90","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.495889Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:98497686010fea20f76ba45d05d68a7eeba9271919bb8e65f2e150ffba6b76fe","observation_id":"81e9ad3e-7541-4592-8557-6237a8ffe466","resolution":{"observed_at":"2026-08-05T18:41:27.667924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:27.321619Z","title":"Mspipe: Efficient temporal gnn training via staleness-aware pipeline","venue":null,"work_id":"48b395e6-6d08-490b-a9be-703be098c69a","year":2024},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.578816Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:4f6f434d4356ac60e6e02ae96ed98ce29e683b5bdd147615861432147f3d5d3e","observation_id":"73c2989b-6f42-4492-bfd1-a86081a574f5","resolution":{"observed_at":"2026-08-05T18:41:27.455711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:27.117230Z","title":"Spectral graph theory","venue":null,"work_id":"df5e335d-e55a-4f10-9710-b27313ace54b","year":2012},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.676845Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:412fb3f833897623a9bea3dc8cbbaa2bca8a2265854d3e0334b7f19c0e7d2734","observation_id":"40b744e5-059b-4f35-b8a2-0d28227c42dd","resolution":{"observed_at":"2026-08-05T18:41:27.214384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:26.915748Z","title":"and Wu, C","venue":null,"work_id":"a5c772a5-18ce-45ec-a703-b1ccec910059","year":2024},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.758964Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:095c4647616ba55a4dc418c0939243babca1859000bfb0de633306b9d43e1571","observation_id":"15afde08-6813-4aea-8047-ea84afb57402","resolution":{"observed_at":"2026-08-05T18:41:27.002575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04284","last_updated":"2024-02-26T09:23:12Z","snapshot_observed_at":"2026-08-13T04:25:34.956606Z","submitted_at":"2024-02-06T01:34:56Z","title":"PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04284","snapshot_observed_at":"2026-08-05T18:41:19.900502Z","title":"Pres: Toward scalable memory-based dynamic graph neural networks, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.900502Z"},"links":{"cited_paper":"/paper/2402.04284","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:e514f94df0c5effa73c6bf64db6b922dc8e029e2d41f52e38e41fa2eb713c89f","observation_id":"92e6498c-eba6-4686-967f-a02e7d57c9c2","resolution":{"observed_at":"2026-08-05T18:41:19.900502Z","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":"2026-08-05T18:41:26.696450Z","title":"and Liu, Y","venue":null,"work_id":"dbae2bd2-9cfb-4ca4-bd73-4995d0d36050","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:19.995077Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:1fb30ab2efeaeca32e719b2bfb99d462992296baf516a46643005ee8b02d3b02","observation_id":"447ca4f4-9e87-4ebe-926b-edb5ce7a69cf","resolution":{"observed_at":"2026-08-05T18:41:26.799822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.14522","last_updated":"2022-11-12T16:11:19Z","snapshot_observed_at":"2026-08-14T07:38:21.479705Z","submitted_at":"2021-11-29T13:27:56Z","title":"Understanding over-squashing and bottlenecks on graphs via curvature","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.14522","snapshot_observed_at":"2026-08-05T18:41:20.063418Z","title":"P., Dong, X., and Bronstein, M","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.063418Z"},"links":{"cited_paper":"/paper/2111.14522","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:d7298b38009f8473767d3d695a2d81f323b9387333e9020e6284e7f345d27f29","observation_id":"15a16c80-36db-4337-b282-1849e5e9dc2d","resolution":{"observed_at":"2026-08-05T18:41:20.063418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.14286","last_updated":"2022-12-06T00:16:17Z","snapshot_observed_at":"2026-08-13T13:48:19.861329Z","submitted_at":"2020-09-29T20:00:31Z","title":"Benign overfitting in ridge regression","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.14286","snapshot_observed_at":"2026-08-05T18:41:20.145764Z","title":"and Bartlett, P","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.145764Z"},"links":{"cited_paper":"/paper/2009.14286","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:f2aa90368a5dab6bb89e2dd9fb4e1364acfdd2dda71b72094d906bef973de5df","observation_id":"6dbbba96-4dc5-4743-9b96-4e90ccab7aa7","resolution":{"observed_at":"2026-08-05T18:41:20.145764Z","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":"2026-08-05T18:41:26.537662Z","title":"and Bartlett, P","venue":null,"work_id":"e74f64c6-8bf8-491a-82f5-285f40a5b7d7","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.226983Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:bb30cebb057772cab5ec1178f280ab41eca000c734ef88d0fff1c89195c08f41","observation_id":"a7610be1-fbc2-49f1-9603-fea6af7ee04f","resolution":{"observed_at":"2026-08-05T18:41:26.604785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:26.367841Z","title":"Compound--protein interaction prediction with end-to-end learning of neural networks for graphs and sequences","venue":null,"work_id":"7cd95e34-59d1-4c06-85e4-ac8ce8b42704","year":2019},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.316583Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:2ce5d652ec69323a95f4d80988a59cce1d8c9056ffd35e394408ee954c2027af","observation_id":"d02a315b-dc1c-438d-8ede-a45a7a3e576d","resolution":{"observed_at":"2026-08-05T18:41:26.442209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:26.171902Z","title":"Graph spectra for complex networks","venue":null,"work_id":"f1cb824b-0a54-441f-a43e-c8b4535f4386","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.380414Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:65cf0a4710fe47d6340462f58770e30b42ee51df30e3d4f0474dc81e4f8b245e","observation_id":"37c9a8ed-8939-4207-aaea-b32a22589ce8","resolution":{"observed_at":"2026-08-05T18:41:26.278503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10903","last_updated":"2018-02-04T19:13:29Z","snapshot_observed_at":"2026-08-13T22:35:40.714745Z","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":"2026-08-05T18:41:20.447935Z","title":"Graph attention networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.447935Z"},"links":{"cited_paper":"/paper/1710.10903","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:d17afad18a50a947e73029d971f476ae0d4d0a0a639cfcde0a4b755dcd914759","observation_id":"1fddeea9-231b-420b-bf10-74086982b9a1","resolution":{"observed_at":"2026-08-05T18:41:20.447935Z","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":"2026-08-05T18:41:25.934075Z","title":"and Zhang, Z.-L","venue":null,"work_id":"a9f222b1-8ed7-4985-b463-d4da53037085","year":2019},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.521066Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:4e60875533955811745b110e1410037890f8f4a12eb5d93c6b85d592cfa6a1fc","observation_id":"9afd97e2-5703-4776-9e88-5a16b68876f4","resolution":{"observed_at":"2026-08-05T18:41:26.044875Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:25.699334Z","title":"and Xu, J","venue":null,"work_id":"4ceee331-8c76-45ae-8857-b3a36d749315","year":2020},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.580948Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:4a9ca9c68c40a43f7301a7331c0e22def68102d8fdc3a0a3113ab54b09881f2a","observation_id":"574cb27d-ad19-4355-8d65-5aa1aed76c5e","resolution":{"observed_at":"2026-08-05T18:41:25.807860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:25.510317Z","title":"Simplifying graph convolutional networks","venue":null,"work_id":"242939fc-f75d-47ea-a83d-30381a8e410c","year":2019},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.648971Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:e928d95e1d9956471d01768805db5763a44dafac7765fbce7b1f6449bbb62bb3","observation_id":"14d1500d-72a0-43a5-88d3-40837ab7c8b4","resolution":{"observed_at":"2026-08-05T18:41:25.611905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:25.280723Z","title":null,"venue":null,"work_id":"b3134c7a-7875-48d8-b4f0-b01135fa7f9a","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.709432Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:2d14ff68ff3bf2e20d2cdce8a1417622ee0adbaafb825b009629e866d6a00722","observation_id":"359db9f4-25c9-4a73-b50a-4e96c82b6b06","resolution":{"observed_at":"2026-08-05T18:41:25.384887Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:25.121262Z","title":"Handling distribution shifts on graphs: An invariance perspective, 2022","venue":null,"work_id":"1272c8c1-7efd-45bf-a566-f49206d5e1d0","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.767662Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:581ed05c9f7bf74d77d26b7e582c7f864d6c118281056d2e2c534651a4175120","observation_id":"07ad373d-0b6e-4033-b6f7-94421808bd90","resolution":{"observed_at":"2026-08-05T18:41:25.193804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:24.951749Z","title":"B., and Fei-Fei, L","venue":null,"work_id":"40d8307e-320d-4c88-9690-ce2e78191635","year":2017},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.860253Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:af938a53f41c62c703be7073aaa2c18428f7b3bad6a0372dd93a65512e226e71","observation_id":"4d48f0fb-43eb-4288-94ea-70446bbb1f6c","resolution":{"observed_at":"2026-08-05T18:41:25.035167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:24.759012Z","title":"and Hsu, D","venue":null,"work_id":"eef8745f-6d6c-4a83-b582-9713140f0724","year":2019},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:20.923500Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:f4afd9ea761ce1e35ff48e5ac7a1fb410871420c11418dc2977928a27e2a9e34","observation_id":"4cafe744-3882-4d6c-bff3-3580771ef422","resolution":{"observed_at":"2026-08-05T18:41:24.860976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.00826","last_updated":"2019-02-22T19:15:54Z","snapshot_observed_at":"2026-08-13T05:06:48.606308Z","submitted_at":"2018-10-01T17:11:31Z","title":"How Powerful are Graph Neural Networks?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.00826","snapshot_observed_at":"2026-08-05T18:41:21.010034Z","title":"How powerful are graph neural networks? arXiv preprint arXiv:1810.00826, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.010034Z"},"links":{"cited_paper":"/paper/1810.00826","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:d885f1c35f32157b1ca65833145dbbd52decb1b0ed060382a841b868b9b9990f","observation_id":"ce8ec512-70ca-4672-a803-6adc64f95142","resolution":{"observed_at":"2026-08-05T18:41:21.010034Z","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":"2026-08-05T18:41:24.530897Z","title":"Z., Guo, Z., Zhou, K., Zhang, W., and Liu, Z","venue":null,"work_id":"1dfe298c-7ef3-47cc-9156-ed02b5a0b387","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.098054Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:5ab09926fa034f29cf1c84f8224922624f2bb3902e744c9111670e56bbbaad6f","observation_id":"1f365408-59f6-4550-9ca3-0670c1b32de1","resolution":{"observed_at":"2026-08-05T18:41:24.653730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:24.218221Z","title":"Neural motifs: Scene graph parsing with global context, 2018","venue":null,"work_id":"21a9d2e7-33e7-4b07-a4a3-91a8bdca54e3","year":2018},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.189003Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:be1ad735edd5dcfadca696723a07811f844ce40c6153327800d309a7ab011c52","observation_id":"edbf1814-2eb2-4ebd-85da-cea663c105d4","resolution":{"observed_at":"2026-08-05T18:41:24.423340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08235","last_updated":"2025-01-10T16:02:22Z","snapshot_observed_at":"2026-08-13T10:33:48.590000Z","submitted_at":"2023-08-16T09:12:21Z","title":"The Expressive Power of Graph Neural Networks: A Survey","version":2},"cited_work":{"arxiv_id":"2308.08235","doi":null,"metadata_source":"pith","pith_arxiv_id":"2308.08235","snapshot_observed_at":"2026-08-05T18:41:21.963304Z","title":"The Expressive Power of Graph Neural Networks: A Survey","venue":"cs.LG","work_id":"8b6d4214-55e1-4515-8fb1-7bf63c765273","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.244827Z"},"links":{"cited_paper":"/paper/2308.08235","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:d5cd905683f49f119d256f99ea42afbd78ae3ca50e6f3cd61179f2679e6a8a35","observation_id":"a1efca9d-d4a9-4483-a920-fc8ab25bc5b3","resolution":{"observed_at":"2026-08-05T18:41:22.035084Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:23.885827Z","title":"A complete expressiveness hierarchy for subgraph gnns via subgraph weisfeiler-lehman tests","venue":null,"work_id":"5629aeb5-b99f-47a3-8a46-eb37f3eb943a","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.301239Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:556227f03fd958d5fdbe68961653a82cdb61c84d99680cc1d7e8bc3f3d612627","observation_id":"0d3f6650-c556-4e11-a6a8-2fa24eb828b8","resolution":{"observed_at":"2026-08-05T18:41:24.030389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.09505","last_updated":"2024-02-11T03:44:23Z","snapshot_observed_at":"2026-08-13T12:59:33.680885Z","submitted_at":"2023-01-23T15:58:59Z","title":"Rethinking the Expressive Power of GNNs via Graph Biconnectivity","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.09505","snapshot_observed_at":"2026-08-05T18:41:21.350824Z","title":"Rethinking the expressive power of gnns via graph biconnectivity","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.350824Z"},"links":{"cited_paper":"/paper/2301.09505","citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:0bee7ef29d4a4343c8dd850017a6e00843456546845afb2686055bf3f5d2cff7","observation_id":"8ff7cf5f-aa9a-4e6c-ba7f-281e8c901ca1","resolution":{"observed_at":"2026-08-05T18:41:21.350824Z","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":"2026-08-05T18:41:23.588073Z","title":null,"venue":null,"work_id":"0e990a52-942e-41eb-8f67-472d5d71e873","year":2022},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.440420Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:83262bae85cd7256a0d5073d8d4e91438d91ea43548f56fa86199f98cbc1bd6a","observation_id":"ce8ac558-f3bc-41c9-8744-2f61a21985a9","resolution":{"observed_at":"2026-08-05T18:41:23.717698Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:23.406092Z","title":"Shift-robust gnns: Overcoming the limitations of localized graph training data, 2021","venue":null,"work_id":"3c9f80ef-1c0d-40cd-beeb-7b5cb7273583","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.507764Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:6e4aeebbb317613462ff3a570349e563988e2b9e538f4fb05417b27647613a85","observation_id":"50d3a005-442f-46ca-9185-a9380f7bcbbe","resolution":{"observed_at":"2026-08-05T18:41:23.481731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:23.246105Z","title":"P., and Kakade, S","venue":null,"work_id":"aed19788-fd5e-477f-8604-962c3f67cff0","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.593164Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:c2f49a3588a8190c10fa7e2d4a33398fdcebbe791bed24b943754bf88d409bc7","observation_id":"fe244dba-ab6b-4cb5-ad63-bad77c4b1cb6","resolution":{"observed_at":"2026-08-05T18:41:23.308716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:23.048932Z","title":"Benign overfitting of constant-stepsize sgd for linear regression","venue":null,"work_id":"12d27cf3-f95c-4ceb-9c87-60a20c82e45d","year":2021},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.689195Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:2840c501aed053f002b4498d8bf8376a654f9fcda8cf5c7df4da22bd148ca3ca","observation_id":"620fbac1-10b8-4818-a207-e92f3d3dbd27","resolution":{"observed_at":"2026-08-05T18:41:23.145889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:22.907255Z","title":null,"venue":null,"work_id":"4d5ef27b-4cc7-40b0-9d72-33b344da2ac4","year":2023},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.777430Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:518dc6ab9809acf3f6fbc26a8175c7dd02cf337de89459f84d7d057a0595a749","observation_id":"b3290784-6d94-4c91-914c-0051c6cf463f","resolution":{"observed_at":"2026-08-05T18:41:22.960965Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-05T18:41:21.823852Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-05T18:41:21.823852Z"},"links":{"citing_paper":"/paper/2508.14338"},"observation_digest":"sha256:cfb06396fb9e652d7ab61326bcc0a0bdb5285e597d07d8b15165da47e153f482","observation_id":"3acbd04a-3c27-46f1-951f-cd0f2aadb6d5","resolution":{"observed_at":"2026-08-05T18:41:21.823852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2508.14338","last_updated":"2025-08-20T01:26:56Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T20:03:59.730297Z","submitted_at":"2025-08-20T01:26:56Z","title":"On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks"},"reference_resolution":{"displayed":79,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":20,"verified_exact":3,"verified_fuzzy":55},"total_outbound_references":79},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2508.14338."}