{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SO2AO57LILXZ6J4XYIQONWJZMM","short_pith_number":"pith:SO2AO57L","schema_version":"1.0","canonical_sha256":"93b40777eb42ef9f2797c220e6d939631e7c975f5997fa6a9ed79ca3dded64d5","source":{"kind":"arxiv","id":"2505.14033","version":2},"attestation_state":"computed","paper":{"title":"Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.NA","eess.SP","math.NA"],"primary_cat":"cs.LG","authors_text":"Guoming Li, Jian Yang, Yifan Chen","submitted_at":"2025-05-20T07:30:45Z","abstract_excerpt":"Filtering-based graph neural networks (GNNs) constitute a distinct class of GNNs that employ graph filters to handle graph-structured data, achieving notable success in various graph-related tasks. Conventional methods adopt a graph-wise filtering paradigm, imposing a uniform filter across all nodes, yet recent findings suggest that this rigid paradigm struggles with heterophilic graphs. To overcome this, recent works have introduced node-wise filtering, which assigns distinct filters to individual nodes, offering enhanced adaptability. However, a fundamental gap remains: a comprehensive frame"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.14033","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-20T07:30:45Z","cross_cats_sorted":["cs.NA","eess.SP","math.NA"],"title_canon_sha256":"1be1008adb76fb39a79e5e239010e8dd4c5d817299ee0080ff6c6e65643ea18f","abstract_canon_sha256":"1937f426f159e381f08a57e28adb57ee6d157bae6c0c73f3252e53f758af3a60"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:07:25.175661Z","signature_b64":"VOErUcwoP0eQUVlFlwVF7VmerLQ/0F/CieUluyX2LGTicGJpe1IgZmnCNTcRNQ+kYDSL/5T+37nPYv3azg3ABQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93b40777eb42ef9f2797c220e6d939631e7c975f5997fa6a9ed79ca3dded64d5","last_reissued_at":"2026-07-05T11:07:25.175112Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:07:25.175112Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.NA","eess.SP","math.NA"],"primary_cat":"cs.LG","authors_text":"Guoming Li, Jian Yang, Yifan Chen","submitted_at":"2025-05-20T07:30:45Z","abstract_excerpt":"Filtering-based graph neural networks (GNNs) constitute a distinct class of GNNs that employ graph filters to handle graph-structured data, achieving notable success in various graph-related tasks. Conventional methods adopt a graph-wise filtering paradigm, imposing a uniform filter across all nodes, yet recent findings suggest that this rigid paradigm struggles with heterophilic graphs. To overcome this, recent works have introduced node-wise filtering, which assigns distinct filters to individual nodes, offering enhanced adaptability. However, a fundamental gap remains: a comprehensive frame"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.14033","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.14033/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.14033","created_at":"2026-07-05T11:07:25.175180+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.14033v2","created_at":"2026-07-05T11:07:25.175180+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.14033","created_at":"2026-07-05T11:07:25.175180+00:00"},{"alias_kind":"pith_short_12","alias_value":"SO2AO57LILXZ","created_at":"2026-07-05T11:07:25.175180+00:00"},{"alias_kind":"pith_short_16","alias_value":"SO2AO57LILXZ6J4X","created_at":"2026-07-05T11:07:25.175180+00:00"},{"alias_kind":"pith_short_8","alias_value":"SO2AO57L","created_at":"2026-07-05T11:07:25.175180+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM","json":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM.json","graph_json":"https://pith.science/api/pith-number/SO2AO57LILXZ6J4XYIQONWJZMM/graph.json","events_json":"https://pith.science/api/pith-number/SO2AO57LILXZ6J4XYIQONWJZMM/events.json","paper":"https://pith.science/paper/SO2AO57L"},"agent_actions":{"view_html":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM","download_json":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM.json","view_paper":"https://pith.science/paper/SO2AO57L","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.14033&json=true","fetch_graph":"https://pith.science/api/pith-number/SO2AO57LILXZ6J4XYIQONWJZMM/graph.json","fetch_events":"https://pith.science/api/pith-number/SO2AO57LILXZ6J4XYIQONWJZMM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM/action/storage_attestation","attest_author":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM/action/author_attestation","sign_citation":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM/action/citation_signature","submit_replication":"https://pith.science/pith/SO2AO57LILXZ6J4XYIQONWJZMM/action/replication_record"}},"created_at":"2026-07-05T11:07:25.175180+00:00","updated_at":"2026-07-05T11:07:25.175180+00:00"}