{"as_of":"2026-08-06T07:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:830443a1264e2c7fbd19b36e9174939656b45f8524213c749bd84f14980e4754","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T15:35:35.400226Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+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/2508.19737/citation-record","integrity":"/paper/2508.19737/integrity","json":"/paper/2508.19737/citation-record.json","paper":"/paper/2508.19737"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T15:35:35.861142Z","title":"Efficient identity and position graph em- bedding via spectral-based random feature aggregation,","venue":null,"work_id":"ad11399f-43ab-4923-a5cd-5787086dd369","year":2025},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.262182Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:0a793f9a4ac0c885b74a5318d81a2e510bed1a65daee98e1b0e96cb9c4fd63d0","observation_id":"a93ca56d-c010-4a5f-8431-65b1b8540841","resolution":{"observed_at":"2026-08-05T15:35:35.865308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.849859Z","title":"20 years of network community detection,","venue":null,"work_id":"a33fa1f3-5789-4e56-ba59-d9fea46cd6a4","year":2022},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.267022Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:dc73a0cd4af5fbd2735c1ec46300964c7ca94443e8dd7aabf00a237700befce6","observation_id":"82d9d125-19c5-4ece-9bca-0a2a9700415d","resolution":{"observed_at":"2026-08-05T15:35:35.854844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.839595Z","title":"Spectral clustering on protein- protein interaction networks via constructing affinity matrix using at- tributed graph embedding,","venue":null,"work_id":"b9c35538-0db6-4672-9dac-a15513c48426","year":2021},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.274633Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:12d6749bab5d32b8d9ab462f56e84dcc59a3ac4b2f22bc14daf1ea0537836d60","observation_id":"266efb17-a416-4d4e-9003-46a43a703530","resolution":{"observed_at":"2026-08-05T15:35:35.843786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.828403Z","title":"Optimal decomposition for large-scale infrastructure- based wireless networks,","venue":null,"work_id":"b7170377-1e28-4652-8fa9-623e01f43f10","year":2017},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.278343Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:3e0cc7bc94cf1222b78f53780151338f483a7298e245fee375404d2e58b82aef","observation_id":"57e28326-377d-437c-bfca-9c86cd67aca5","resolution":{"observed_at":"2026-08-05T15:35:35.833482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.818614Z","title":"Graph partitioning models for parallel computing,","venue":null,"work_id":"8ba7231c-8226-4d26-9ae5-6546cdb31592","year":2000},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.282363Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:74f019b15d96c6147a6b4a9f26eb4d9904f1e9d3f702b041a64761af13bd618f","observation_id":"c3abc0bd-87d3-4b48-9a1f-39881e16e31e","resolution":{"observed_at":"2026-08-05T15:35:35.822404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.808447Z","title":"Towards a profiling view for unsupervised traffic classification by exploring the statistic features and link patterns,","venue":null,"work_id":"386b637c-2e87-4c50-99e0-778ce90fbbc2","year":2019},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.286173Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:eb61538b4565dcc8dc3720740536ff35f33102778e6c7dbe6a94242339a694e4","observation_id":"6cea444d-a9db-4114-8634-21562e63d98a","resolution":{"observed_at":"2026-08-05T15:35:35.813074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.798971Z","title":"Streaming graph challenge: Stochastic block partition,","venue":null,"work_id":"1eb5d0d9-4f40-42c6-8a13-aeb8c4c2f6d0","year":2017},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.291431Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:f3a8c722ebdaa3d40ccadcefcd6aacf02b4723b1837e92f5e4a1f1a621a757fe","observation_id":"2beab181-7287-4aed-803b-76c4686d15e1","resolution":{"observed_at":"2026-08-05T15:35:35.802829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.788483Z","title":"Fast stochastic block partitioning via sampling,","venue":null,"work_id":"424f7da3-5ddb-45b7-8c19-e33290518c68","year":2019},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.295284Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:fdea13b917a9aad088babd250edb68019c368cf34980d768779cdbe6c29408e1","observation_id":"08904ced-20ed-4c88-9eb3-3d13805b79b2","resolution":{"observed_at":"2026-08-05T15:35:35.792015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.711605Z","title":"An integrated ap- proach for accelerating stochastic block partitioning,","venue":null,"work_id":"5f45ac65-04d0-456a-b439-afd11d5cf245","year":2023},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.298455Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:d6b80107c8f014d4ed77a01cdc9936d01e4d8ed43438721a4a99e1d882b6a781","observation_id":"a8767fa4-a1a6-4774-87d5-a33ebc563ace","resolution":{"observed_at":"2026-08-05T15:35:35.715709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.700485Z","title":"Kalman filter driven estimation of com- munity structure in time varying graphs,","venue":null,"work_id":"dbd7e8aa-58fe-41d7-927c-cd5b6f1112e6","year":2022},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.302304Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:955f995df03a0049791d1a311705a91330aef81cd5e6bb7e273ae2b9006cfe4d","observation_id":"ed72ac68-a7e7-4e3b-b362-83ef0344789f","resolution":{"observed_at":"2026-08-05T15:35:35.704941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.688074Z","title":"Preconditioned spectral clustering for stochastic block partition streaming graph challenge,","venue":null,"work_id":"2657c825-727b-4d44-94a5-d8dcde1e2ac3","year":2017},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.305669Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:ed474518e355c63d49096413ba1454a86069dd77854cbc018cc47eea7f323a81","observation_id":"9cf13e82-b82a-4e55-81e7-9868264cb2ec","resolution":{"observed_at":"2026-08-05T15:35:35.693823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.676741Z","title":"Raftgp: Random fast graph partitioning,","venue":null,"work_id":"60e23686-05ff-44f2-a768-5bde08f7650e","year":2023},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.309565Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:8e8c0fbad0469af0f5e4712c2ae62d5a18d2fabebebb482e2b445321f8fccc06","observation_id":"8c2e1ab3-9ce4-4aa0-bb88-79a60b71f8b0","resolution":{"observed_at":"2026-08-05T15:35:35.681232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.665768Z","title":"Towards faster graph partitioning via pre-training and inductive inference,","venue":null,"work_id":"4f2652dc-fc9a-4f0c-9f71-8c7c4b69801d","year":2024},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.313284Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:1f03e3b6be409a6cfdfd5df94ef061467df388bd6fba92ec1d9b69802c693dcf","observation_id":"667611eb-2bd5-4096-8300-332f208acd13","resolution":{"observed_at":"2026-08-05T15:35:35.670263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.652699Z","title":"An information flow model for conflict and fission in small groups,","venue":null,"work_id":"15e9c8a8-78b5-4810-8b60-3c13b87e11e2","year":1977},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.316984Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:74874b7fa712ea0e7f84da79f8e09136618a82b1aa63c1ee860a2844f8e81ef8","observation_id":"4092aca8-9c01-4550-91e8-9a894196fe18","resolution":{"observed_at":"2026-08-05T15:35:35.658846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.641150Z","title":"The emerging field of signal processing on graphs: Ex- tending high-dimensional data analysis to networks and other irregular domains,","venue":null,"work_id":"899a46d7-9a29-4817-aa38-0859d7156b31","year":2013},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.322435Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:5f04156a48ee1ea866ebf404d66c05c4099fe07ff6aeff1807e44b6efed49490","observation_id":"2d8c4b35-fa03-4521-9857-5a367663edb8","resolution":{"observed_at":"2026-08-05T15:35:35.645852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.628376Z","title":"A tutorial on spectral clustering,","venue":null,"work_id":"bd5e16a3-4c49-41ce-8e76-a441cc481557","year":2007},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.326173Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:8a93896a9d134941e9badcf483f2b1e33989e3539a190d39624915032f7ed65c","observation_id":"4e3bda00-c19f-4efc-9c01-ba45e6ca46dc","resolution":{"observed_at":"2026-08-05T15:35:35.632561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.615831Z","title":"Pacer: Network embedding from positional to structural,","venue":null,"work_id":"70aee1b0-a0f6-4539-bbbe-80adade57389","year":2024},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.329888Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:9b36f421e57409c1e37166ef45ae0fe2f60f55e16025fe007e8882a4cae1d190","observation_id":"11db9b75-d29c-42bf-a741-96a9b6792f56","resolution":{"observed_at":"2026-08-05T15:35:35.620197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.605459Z","title":"Irwe: Inductive random walk for joint inference of identity and position network embedding,","venue":null,"work_id":"8f9b23c2-4d48-4e57-a34e-360ddf369a83","year":2024},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.333990Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:0736d7a9c18ce4dba02bff4c563fff30f103b0e99944943955973487858f97a3","observation_id":"b9a629a6-6acb-442d-a3d5-d6d08c47bba9","resolution":{"observed_at":"2026-08-05T15:35:35.609523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.593505Z","title":"Gershgorin disks for multiple eigenvalues of non-negative matrices,","venue":null,"work_id":"f0592a27-5d0d-4d68-a3bd-c92ebd124f22","year":2017},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.338145Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:a52c7ba7e2a37a19c87b05afed05d9281b480b28eda745690cff8e78d943145a","observation_id":"fc8e873d-9f8c-4876-b4b2-bf1fce18086a","resolution":{"observed_at":"2026-08-05T15:35:35.597855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.582713Z","title":"Birch: an efficient data clustering method for very large databases,","venue":null,"work_id":"af757a24-4cef-4898-82c3-d20179c602f2","year":1996},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.341979Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:2fb9c48712e1e3e9c6e51a622215c831e213955f0c268211c3aa6036886bf4b3","observation_id":"30d0a7dd-ef14-4929-a37a-a0a19769d80a","resolution":{"observed_at":"2026-08-05T15:35:35.587123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.572825Z","title":"Beyond low-frequency infor- mation in graph convolutional networks,","venue":null,"work_id":"67e39655-6b04-403a-8827-25409ca8dd0b","year":2021},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.346761Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:c16a163dde19d41f4fbba82d40bbd27b9058f33eb3f1be8d55da5447680932b6","observation_id":"fc56b92a-84ae-4e9c-b1e6-3f574705ded7","resolution":{"observed_at":"2026-08-05T15:35:35.576844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.562548Z","title":"Adagnn: Graph neural networks with adaptive frequency response filter,","venue":null,"work_id":"2598f21b-c007-44e9-976a-4ee0b97d53b5","year":2021},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.350577Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:e092f2eb635fff48422db6fd496495b462aa9fe7b3d1b223510c40c5b36a6322","observation_id":"35919ee3-ef9f-4efd-b02e-44ed6d4b2f99","resolution":{"observed_at":"2026-08-05T15:35:35.566713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.549892Z","title":"Towards a better tradeoff between quality and efficiency of community detection: an inductive embedding method across graphs,","venue":null,"work_id":"920b8f27-eacd-43cf-a469-616773e63051","year":2023},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.355927Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:71abb248b98f449810404189c10c34359a34e18d543a067e1b1325c8eefbc734","observation_id":"3503b5d8-b283-4f5c-966f-3f03651081b9","resolution":{"observed_at":"2026-08-05T15:35:35.554441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.539261Z","title":"Efficient monte carlo and greedy heuristic for the inference of stochastic block models,","venue":null,"work_id":"275a29f1-2139-4a1e-86ea-165bd0ade595","year":2014},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.360056Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:e35b6ff6377dccdaa1d2663df7452368245afdb6981bcf4e9cd7be53a35c4d7b","observation_id":"daea4707-1669-4a23-9b9c-a350c016ef00","resolution":{"observed_at":"2026-08-05T15:35:35.543666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.528303Z","title":"A scalable community detection algorithm for large graphs using stochastic block models,","venue":null,"work_id":"7f869aff-81d8-4c76-b916-50bced916253","year":2015},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.364546Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:c8ad230ea7fc698d6bf133154239cf9bdd0c00277b7c38cd19b09e6d9e45fa1e","observation_id":"48d0eca5-616d-4e2d-883a-635bcb28c083","resolution":{"observed_at":"2026-08-05T15:35:35.532613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.517216Z","title":"Fast unfolding of communities in large networks,","venue":null,"work_id":"cba28600-a772-45fb-bef0-acd0c19c8839","year":2008},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.368359Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:a3507d4be8580c424801b93d61c69af7feeafef2d1e2362f0da7f1b2172275da","observation_id":"864c7fc3-abf6-4453-8b0c-395d802c0556","resolution":{"observed_at":"2026-08-05T15:35:35.521270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.504378Z","title":"Community detection using fast low- cardinality semidefinite programming,","venue":null,"work_id":"3c15ab15-e08e-44af-99ec-6ad0dcca3eb1","year":2020},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.372164Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:9f8e5e5fa05549115935381ea316d1765e181467b9f6328905aa9998a556da10","observation_id":"49a29567-8a3e-4c1c-943c-096e5ac3e5a6","resolution":{"observed_at":"2026-08-05T15:35:35.510928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-05T15:35:35.376135Z","title":"Semi-supervised classification with graph convolutional networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.376135Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:f463c3871ac949fa29ef29493cce2924d319a134542626179ac4cea427367414","observation_id":"f806cd12-c991-4a67-9a7f-52fa74f92b8d","resolution":{"observed_at":"2026-08-05T15:35:35.376135Z","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":"2026-08-05T15:35:35.491367Z","title":"Adaptive community detection incorporating topology and content in social net- works,","venue":null,"work_id":"ed20bb16-e5ec-4f46-b33d-e98fe18d097b","year":2018},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.380680Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:55fa4c377472413420fb206cb4342c1c9bd85e40b3d95781899ebc6f76ee2443","observation_id":"9e0749f3-3e70-4804-9a32-16a5f8df7376","resolution":{"observed_at":"2026-08-05T15:35:35.495896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.479535Z","title":"Community detection in node-attributed social networks: How structure-attributes correlation affects clustering quality,","venue":null,"work_id":"33c40b88-9298-457f-8e0e-56a8f26b196c","year":2020},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.384390Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:1256f44319bac894d53314edee8e41171792897deae548221756d21c91640d26","observation_id":"cd8cc6d3-ca80-47d3-b908-6fd3a0120e5f","resolution":{"observed_at":"2026-08-05T15:35:35.483793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.467872Z","title":"Dual-channel hybrid community detection in attributed networks,","venue":null,"work_id":"da9298b6-9d8d-4151-8b10-824f46b00308","year":2021},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.389297Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:4895e326beec341695e261b3e9058aafe60903872d7fca3c510f71bedc57e5fe","observation_id":"b9ecf9ea-c110-43dd-80aa-41dc994d60ed","resolution":{"observed_at":"2026-08-05T15:35:35.472384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.456573Z","title":"The trade-off between topology and content in community detection: An adaptive encoder–decoder-based nmf approach,","venue":null,"work_id":"85a835cf-b934-48e1-ae3c-edf2f80abb5c","year":2022},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.392743Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:6aca0aaa14ca97c4ee39e5dc555e77a2a0c791c39f26afbeffb7ada56aa03414","observation_id":"20bc2f56-4a48-404f-a681-63e80d85453d","resolution":{"observed_at":"2026-08-05T15:35:35.460915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.443131Z","title":"High-quality temporal link prediction for weighted dynamic graphs via inductive embedding aggregation,","venue":null,"work_id":"59328483-4170-491a-9345-b6a68c0f0728","year":2023},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.396211Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:af1a11029cac1a9133227a0f2e6ac489a925305fed724a5b623c0ed02f605d86","observation_id":"49e606e6-d606-44f0-8d62-1d9750066a21","resolution":{"observed_at":"2026-08-05T15:35:35.449904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-05T15:35:35.428575Z","title":"Temporal link prediction: A unified frame- work, taxonomy, and review,","venue":null,"work_id":"bc06a787-3314-4cc1-836b-744b3afecce2","year":2023},"citing_paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T15:35:35.400226Z"},"links":{"citing_paper":"/paper/2508.19737"},"observation_digest":"sha256:fd93d587c421c229ebb8b6a7e39c67950d0f5598a69af135f054049990f68902","observation_id":"7420bb46-a695-4ac5-abd1-d4cd8d94236b","resolution":{"observed_at":"2026-08-05T15:35:35.434580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.19737","last_updated":"2025-08-27T10:07:34Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T15:35:34.723920Z","submitted_at":"2025-08-27T10:07:34Z","title":"InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":33},"total_outbound_references":34},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2508.19737."}