{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:KWV3SORYZ4CKHJR7I3733ITUCN","short_pith_number":"pith:KWV3SORY","schema_version":"1.0","canonical_sha256":"55abb93a38cf04a3a63f46ffbda274136cd76e8d2ee39b63b3d3f12e96f1c533","source":{"kind":"arxiv","id":"2502.03703","version":1},"attestation_state":"computed","paper":{"title":"On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Qiao Zhang, Runzhong Wang, Ziang Chen","submitted_at":"2025-02-06T01:25:22Z","abstract_excerpt":"Graph neural networks (GNNs) have been widely used in graph-related contexts. It is known that the separation power of GNNs is equivalent to that of the Weisfeiler-Lehman (WL) test; hence, GNNs are imperfect at identifying all non-isomorphic graphs, which severely limits their expressive power. This work investigates $k$-hop subgraph GNNs that aggregate information from neighbors with distances up to $k$ and incorporate the subgraph structure. We prove that under appropriate assumptions, the $k$-hop subgraph GNNs can approximate any permutation-invariant/equivariant continuous function over gr"},"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":"2502.03703","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-06T01:25:22Z","cross_cats_sorted":[],"title_canon_sha256":"ed4eda73a6950e28d5a2f2305d39fd434a71f42827b8770cc07570bdee533f5f","abstract_canon_sha256":"7aada7a159e5d1eb0499c5795af4f742d41f49af68f52b43355a391dc5cd2469"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:10:13.983591Z","signature_b64":"Xn1HoxItbtakP3BVjHUelmT7yzy29ZJ8wxYF2xIqdeyt2o8of+eSk2kGGkw5m3LAPdaJ7ok4rdqThhgEXF89Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55abb93a38cf04a3a63f46ffbda274136cd76e8d2ee39b63b3d3f12e96f1c533","last_reissued_at":"2026-07-05T10:10:13.983169Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:10:13.983169Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Qiao Zhang, Runzhong Wang, Ziang Chen","submitted_at":"2025-02-06T01:25:22Z","abstract_excerpt":"Graph neural networks (GNNs) have been widely used in graph-related contexts. It is known that the separation power of GNNs is equivalent to that of the Weisfeiler-Lehman (WL) test; hence, GNNs are imperfect at identifying all non-isomorphic graphs, which severely limits their expressive power. This work investigates $k$-hop subgraph GNNs that aggregate information from neighbors with distances up to $k$ and incorporate the subgraph structure. We prove that under appropriate assumptions, the $k$-hop subgraph GNNs can approximate any permutation-invariant/equivariant continuous function over gr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.03703","kind":"arxiv","version":1},"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/2502.03703/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":"2502.03703","created_at":"2026-07-05T10:10:13.983224+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.03703v1","created_at":"2026-07-05T10:10:13.983224+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.03703","created_at":"2026-07-05T10:10:13.983224+00:00"},{"alias_kind":"pith_short_12","alias_value":"KWV3SORYZ4CK","created_at":"2026-07-05T10:10:13.983224+00:00"},{"alias_kind":"pith_short_16","alias_value":"KWV3SORYZ4CKHJR7","created_at":"2026-07-05T10:10:13.983224+00:00"},{"alias_kind":"pith_short_8","alias_value":"KWV3SORY","created_at":"2026-07-05T10:10:13.983224+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/KWV3SORYZ4CKHJR7I3733ITUCN","json":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN.json","graph_json":"https://pith.science/api/pith-number/KWV3SORYZ4CKHJR7I3733ITUCN/graph.json","events_json":"https://pith.science/api/pith-number/KWV3SORYZ4CKHJR7I3733ITUCN/events.json","paper":"https://pith.science/paper/KWV3SORY"},"agent_actions":{"view_html":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN","download_json":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN.json","view_paper":"https://pith.science/paper/KWV3SORY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.03703&json=true","fetch_graph":"https://pith.science/api/pith-number/KWV3SORYZ4CKHJR7I3733ITUCN/graph.json","fetch_events":"https://pith.science/api/pith-number/KWV3SORYZ4CKHJR7I3733ITUCN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN/action/storage_attestation","attest_author":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN/action/author_attestation","sign_citation":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN/action/citation_signature","submit_replication":"https://pith.science/pith/KWV3SORYZ4CKHJR7I3733ITUCN/action/replication_record"}},"created_at":"2026-07-05T10:10:13.983224+00:00","updated_at":"2026-07-05T10:10:13.983224+00:00"}