{"as_of":"2026-08-07T18:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c6f261df79001837113cc415cb4b380868925a014715cc17cc0a29e6009de224","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T17:24:45.132538Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2603.26136/citation-record","integrity":"/paper/2603.26136/integrity","json":"/paper/2603.26136/citation-record.json","paper":"/paper/2603.26136"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:44.963277Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.963277Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:6434558758d7806e5251ac9240b470fa500b2cbb8a95ed3135aa5d58e5fd7abe","observation_id":"5278e7d1-837f-44be-ac6a-1a36dc12e40e","resolution":{"observed_at":"2026-08-02T17:24:44.963277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.02797","last_updated":"2018-09-15T08:31:50Z","snapshot_observed_at":"2026-07-06T06:59:57.168051Z","submitted_at":"2018-09-08T13:08:26Z","title":"Fast Gradient Attack on Network Embedding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.02797","snapshot_observed_at":"2026-08-02T17:24:44.968546Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.968546Z"},"links":{"cited_paper":"/paper/1809.02797","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:83921eba8b70fb729334ee533f4d8b81fafd2b34c19e10994a2ba49236dd3c4e","observation_id":"0b344108-1492-495b-b39b-2d5d73ecd3e6","resolution":{"observed_at":"2026-08-02T17:24:44.968546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.05730","last_updated":"2022-04-05T12:54:56Z","snapshot_observed_at":"2026-08-07T09:25:51.003050Z","submitted_at":"2020-03-10T12:48:00Z","title":"A Survey of Adversarial Learning on Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.05730","snapshot_observed_at":"2026-08-02T17:24:44.973280Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.973280Z"},"links":{"cited_paper":"/paper/2003.05730","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:b5ea28b5d827e343f57920c97ae16de074a51ab61b6e5aaf058ed23907b14115","observation_id":"f8c91c78-6946-4cad-928d-0ddf9a28dea9","resolution":{"observed_at":"2026-08-02T17:24:44.973280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.08057","last_updated":"2022-04-05T05:46:22Z","snapshot_observed_at":"2026-08-06T10:25:52.026656Z","submitted_at":"2022-02-16T13:41:39Z","title":"Understanding and Improving Graph Injection Attack by Promoting Unnoticeability","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.08057","snapshot_observed_at":"2026-08-02T17:24:44.978166Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.978166Z"},"links":{"cited_paper":"/paper/2202.08057","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:da97c3de87df0d4d0d141bcbd1e63a3a16bb6803483ecb253977f83aedd94a12","observation_id":"8a15cf60-4876-48d8-acfe-d56b0fbfc58c","resolution":{"observed_at":"2026-08-02T17:24:44.978166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:44.982973Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.982973Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:8d20d6af6d2c43748af31a552b2ab61e1d209c85c87da49eecc43ae4b2e33e64","observation_id":"b0e3ac0d-aa68-4f4a-a191-8c36b3298de0","resolution":{"observed_at":"2026-08-02T17:24:44.982973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:44.991973Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.991973Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:23814d3f06bab4ea1973c75e15fc6476b92885d97833e7b7bbc0c5f535b0a2e8","observation_id":"6f3682a0-b8fa-47b0-9630-4d184a4a45be","resolution":{"observed_at":"2026-08-02T17:24:44.991973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:44.996159Z","title":"2022.𝑝-Laplacian Based Graph Neural Networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.996159Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:5871a8910ec2083779127a0f193526ec042b72115e3f5221512c9288102c3ad3","observation_id":"65ce7699-1d31-4646-8c43-7b814e31ba00","resolution":{"observed_at":"2026-08-02T17:24:44.996159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.000611Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.000611Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:eb0084966a2906fdbb44433a216ab0132d73b7af32d20b22dfd7f1a051c16869","observation_id":"b65544f8-2fda-458a-a9bb-542b88edb1c5","resolution":{"observed_at":"2026-08-02T17:24:45.000611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.004638Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.004638Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:b4b4860e54f13304eea09cd514d8d402e257a5fb6549b40962446fa6bc36a658","observation_id":"f267200d-6b38-4bd7-a5e2-a2156461b0af","resolution":{"observed_at":"2026-08-02T17:24:45.004638Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.013057Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.013057Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:63d44d3f9291871cc4aab692c243d10d28100403753457e93487b3cc426883c0","observation_id":"a6b42539-4636-4802-91e2-36754fe3a29e","resolution":{"observed_at":"2026-08-02T17:24:45.013057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.008854Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.008854Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:afdfed189dd9e2d41c1d5e1aa346f949bb2da3a7ef2f8a9130ffad07610880be","observation_id":"3ed747cd-efb2-469a-97e9-32768fcfd6d5","resolution":{"observed_at":"2026-08-02T17:24:45.008854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.021089Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.021089Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:d2a5cbe26c4b1b2187ccebe87f7328b8aac787c13a964a29194f54c9d4975808","observation_id":"285381e3-0645-4baf-9a36-26ff9480566a","resolution":{"observed_at":"2026-08-02T17:24:45.021089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.017103Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.017103Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:073385295b7790ff60e5f3b1b9dca9bac21faf80287cc787db313e39a323c705","observation_id":"df8e64aa-6837-4f10-be3f-746465d23395","resolution":{"observed_at":"2026-08-02T17:24:45.017103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-02T17:24:45.029418Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.029418Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:c18ae6047dfc18d23e072b098f1c1020c93a229250a9b4287d29afb0b908deb2","observation_id":"bb39a500-8bdb-45e1-bec0-ff72c0f6ad4d","resolution":{"observed_at":"2026-08-02T17:24:45.029418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.025179Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.025179Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:28464a8733df7650b4e9c36de3ae7add79c97b0cfb62d4ae3b17bf96c3cdeac3","observation_id":"7bd61df3-4313-4375-8920-535b80d7d902","resolution":{"observed_at":"2026-08-02T17:24:45.025179Z","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":"2026-08-02T17:24:45.038834Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.038834Z"},"links":{"cited_paper":"/paper/1707.01926","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:4420db4e0166695033446609115293d860e596f8191dbaa2dc91fdb416c0a966","observation_id":"a53e8cad-ea81-4816-9651-2cdf7fadb82f","resolution":{"observed_at":"2026-08-02T17:24:45.038834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-02T17:24:45.033937Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.033937Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:7446bed3c8ed3e7a21c499f7f3fbb17dd590ad34636887af9a286dc6d795048f","observation_id":"c65a2c1f-0942-4d82-805e-42cdbd5ca2ce","resolution":{"observed_at":"2026-08-02T17:24:45.033937Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.08663","last_updated":"2020-07-16T21:46:33Z","snapshot_observed_at":"2026-08-06T13:06:20.395369Z","submitted_at":"2020-07-16T21:46:33Z","title":"TUDataset: A collection of benchmark datasets for learning with graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.08663","snapshot_observed_at":"2026-08-02T17:24:45.048625Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.048625Z"},"links":{"cited_paper":"/paper/2007.08663","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:bc9d07c4b6e1690883a8ae1e5b85d9456bd975b043b5f87dc323059ff717c38c","observation_id":"5d4b817e-c093-4b06-b619-df897bf6be7b","resolution":{"observed_at":"2026-08-02T17:24:45.048625Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01936","last_updated":"2025-02-04T02:11:57Z","snapshot_observed_at":"2026-07-06T20:30:40.963009Z","submitted_at":"2025-02-04T02:11:57Z","title":"Query-Based and Unnoticeable Graph Injection Attack from Neighborhood Perspective","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.01936","snapshot_observed_at":"2026-08-02T17:24:45.043933Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.043933Z"},"links":{"cited_paper":"/paper/2502.01936","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:a4961c093885151f33a39a79cac56ac232c7757fcd101465aff8050fb9603397","observation_id":"f9e9935d-502b-4109-aed6-134502fbcf2d","resolution":{"observed_at":"2026-08-02T17:24:45.043933Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.056782Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.056782Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:dedfb3219a1fc961cba1056a3bedfbd086bb829f3af8893a4e4a8a9346588d08","observation_id":"205eb28d-05c1-4152-8769-9cf13056eca7","resolution":{"observed_at":"2026-08-02T17:24:45.056782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.052788Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.052788Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:410fb8a7512d00d68e65044da7485e756396c1fe7f9d6fae225a49ff1ce6f525","observation_id":"fe61a238-8c3f-4969-84d0-b942d09003a7","resolution":{"observed_at":"2026-08-02T17:24:45.052788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.065133Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.065133Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:80512d26f5174dae24137fb0c6be2155bddd5659f7464a202fb71d8821a610ed","observation_id":"5f8089ff-65ad-4b39-bf81-fb71f4b438da","resolution":{"observed_at":"2026-08-02T17:24:45.065133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.060807Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.060807Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:fbe2eb9f6f13063ea474c73e7452794c443c79cee402b844f7b281816e159588","observation_id":"078fdc1e-470e-49e8-930a-bd6b719c7e4b","resolution":{"observed_at":"2026-08-02T17:24:45.060807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.077627Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.077627Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:d9304c7d2fef6c4e0ce458e6b7ef254750ea3ed6c43ad237642470b662dabb13","observation_id":"68efada8-d954-467d-b41f-fe7e73e8e6d9","resolution":{"observed_at":"2026-08-02T17:24:45.077627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.081975Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.081975Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:1eb3c5c49ed640583a1fb1038568d7db5327bd515c93e3d05131af7fcdfee5bb","observation_id":"a678b776-4d8a-44eb-9714-306498cc63a0","resolution":{"observed_at":"2026-08-02T17:24:45.081975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.073396Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.073396Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:d417959c839cd60bf65f25cc5cd7bf50202a2125be37484b0a3687b60fa76c84","observation_id":"81015717-e627-47a0-b427-bde067979e95","resolution":{"observed_at":"2026-08-02T17:24:45.073396Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.06757","last_updated":"2021-08-31T03:52:53Z","snapshot_observed_at":"2026-07-06T10:23:43.246202Z","submitted_at":"2020-12-12T08:52:56Z","title":"Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.06757","snapshot_observed_at":"2026-08-02T17:24:45.091048Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.091048Z"},"links":{"cited_paper":"/paper/2012.06757","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:56c6d10a8e9e7dd538d87e3e071aaa1c819ecbc6685793d47f3f0ce831eda961","observation_id":"715e8580-6f85-4aae-ac9e-9e4745ecb597","resolution":{"observed_at":"2026-08-02T17:24:45.091048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.00826","last_updated":"2019-02-22T19:15:54Z","snapshot_observed_at":"2026-07-06T07:05:24.565760Z","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":"2026-08-02T17:24:45.095410Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.095410Z"},"links":{"cited_paper":"/paper/1810.00826","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:97048caf075a826ffc557b834c792561c6acc6dce0c7217098af284f4e62df68","observation_id":"51e11eaf-87d9-4a96-aa1f-fef1830f524c","resolution":{"observed_at":"2026-08-02T17:24:45.095410Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.086740Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.086740Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:4faa2648026e18af51c50f78ac7a1816424b8ca04a27579e3ce21442e630b56e","observation_id":"0dc6b8f1-0ffb-47f7-8556-7452c5d9fb0f","resolution":{"observed_at":"2026-08-02T17:24:45.086740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.104036Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.104036Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:44bc4b3806b3ae21db3c2a2d615da45fe1fa8d8a6e1c29e6d88e1ec1f2907c6c","observation_id":"1491e407-c169-43c7-9ec5-eed4fdc05cae","resolution":{"observed_at":"2026-08-02T17:24:45.104036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.13244","last_updated":"2023-11-22T09:02:04Z","snapshot_observed_at":"2026-07-06T16:50:58.750467Z","submitted_at":"2023-11-22T09:02:04Z","title":"Hard Label Black Box Node Injection Attack on Graph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.13244","snapshot_observed_at":"2026-08-02T17:24:45.107997Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.107997Z"},"links":{"cited_paper":"/paper/2311.13244","citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:6e1930fc0f27e9fc7357a1b0b498c90cedcc2e535f9177671892904d94063f4c","observation_id":"3c2c3ae7-1d26-4199-98c8-c60d19f12ee6","resolution":{"observed_at":"2026-08-02T17:24:45.107997Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.100020Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.100020Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:d45550eae8cb2dae1859e6c437a979c3842ba43f185321512d344b1fd82f955c","observation_id":"8472f0b1-d0cc-40b1-986d-a2cf52c930f8","resolution":{"observed_at":"2026-08-02T17:24:45.100020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.116119Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.116119Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:f7759a15fb2d0f4aeff39a2c111a4a221390b60e5f6f35d135b86696f1ea2cc0","observation_id":"d7c0c4e9-47d3-4fb6-831e-92c1ac296e93","resolution":{"observed_at":"2026-08-02T17:24:45.116119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.119977Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.119977Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:6973187c0db16a2710564bc3c17838570fe65d93b09c5701c55eb11dea7fecb2","observation_id":"8ca5694d-fe05-4ec2-a894-3d75978bd59b","resolution":{"observed_at":"2026-08-02T17:24:45.119977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.112028Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.112028Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:53dea24c2ff8b83b8c229313b2c419fa5b130e7dbc08c3e5b0fe6286e5950340","observation_id":"27ece0a5-4634-4105-ac9a-e24f641ed35b","resolution":{"observed_at":"2026-08-02T17:24:45.112028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.124457Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.124457Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:23836bfd503434c6d7750127e1ccbdeb56e15b8c4ee5415da7c8c6b4f7e35314","observation_id":"be8cacb2-b388-4e06-917d-cc3e3cd7dbdc","resolution":{"observed_at":"2026-08-02T17:24:45.124457Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.128237Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.128237Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:df3a938e90877afc85bd2575675e04390d6259c3919800457e1e8b06e5ec2a89","observation_id":"0f3b6017-c1fc-45b9-919d-6b1527d0ea8d","resolution":{"observed_at":"2026-08-02T17:24:45.128237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.132538Z","title":"We also use early stopping here with the same patience of100epochs","venue":null,"work_id":null,"year":2049},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.132538Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:eb1019db85d9de05abff89514a00c352c24cba6cdc54a7364dc05923e680eb7d","observation_id":"046e50b5-c43c-450e-bc88-e95a299008b2","resolution":{"observed_at":"2026-08-02T17:24:45.132538Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:44.987182Z","title":"InInternational conference on machine learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:44.987182Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:10672aebb80f27ccc37f89e895702b771d3b498edeebd6d442317391bebc4a04","observation_id":"8246d5b2-1913-44ec-926e-c194bf75f7b5","resolution":{"observed_at":"2026-08-02T17:24:44.987182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T17:24:45.069227Z","title":"InProceedings of the Web Conference","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","version":3},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-02T17:24:45.069227Z"},"links":{"citing_paper":"/paper/2603.26136"},"observation_digest":"sha256:2d2fe88eb0b79e84856c1363d80abebbf1b69ec2689d9a9558ac9fd15141d399","observation_id":"a77e78be-ff43-4835-aeb9-ee6b5cdb9f31","resolution":{"observed_at":"2026-08-02T17:24:45.069227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2603.26136","last_updated":"2026-07-28T09:17:19Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T12:18:32.926162Z","submitted_at":"2026-03-27T07:40:10Z","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":39,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":40},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2603.26136."}