{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:62AZYN4OG3EMKMD7WEWIQHMTDA","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"54ab32ff2d86de9f028506412d039eb3da51a49c19a8263fb7dd7e11481d588c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-10T15:33:53Z","title_canon_sha256":"0627eb0e640bd36efaafd88f975d15577afc1b69b74f66ac78c3f8aea688ecb6"},"schema_version":"1.0","source":{"id":"2507.07854","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.07854","created_at":"2026-07-05T11:39:56Z"},{"alias_kind":"arxiv_version","alias_value":"2507.07854v2","created_at":"2026-07-05T11:39:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.07854","created_at":"2026-07-05T11:39:56Z"},{"alias_kind":"pith_short_12","alias_value":"62AZYN4OG3EM","created_at":"2026-07-05T11:39:56Z"},{"alias_kind":"pith_short_16","alias_value":"62AZYN4OG3EMKMD7","created_at":"2026-07-05T11:39:56Z"},{"alias_kind":"pith_short_8","alias_value":"62AZYN4O","created_at":"2026-07-05T11:39:56Z"}],"graph_snapshots":[{"event_id":"sha256:8fb89a663780dfbfeb83e0c534b4b37380eaabe9bd7874c56a2ece19d4c59f12","target":"graph","created_at":"2026-07-05T11:39:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.07854/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Small and Medium-sized Enterprises (SMEs) are vital to the modern economy, yet their credit risk analysis often struggles with scarce data, especially for online lenders lacking direct credit records. This paper introduces a Graph Neural Network (GNN)-based framework, leveraging SME interactions from transaction and social data to map spatial dependencies and predict loan default risks. Tests on real-world datasets from Discover and Ant Credit (23.4M nodes for supply chain analysis, 8.6M for default prediction) show the GNN surpasses traditional and other GNN baselines, with AUCs of 0.995 and ","authors_text":"Huijie Shen, Qianying Liu, Qinyan Shen, Zhuohuan Hu, Zizhou Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-10T15:33:53Z","title":"Credit Risk Analysis for SMEs Using Graph Neural Networks in Supply Chain"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.07854","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:965f12ae0a7eb1755280b11025209c1dd50577ed01d388abcc109415e399f312","target":"record","created_at":"2026-07-05T11:39:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"54ab32ff2d86de9f028506412d039eb3da51a49c19a8263fb7dd7e11481d588c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-10T15:33:53Z","title_canon_sha256":"0627eb0e640bd36efaafd88f975d15577afc1b69b74f66ac78c3f8aea688ecb6"},"schema_version":"1.0","source":{"id":"2507.07854","kind":"arxiv","version":2}},"canonical_sha256":"f6819c378e36c8c5307fb12c881d93180d940cba31f7f09b5aade56f9f6d7e45","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f6819c378e36c8c5307fb12c881d93180d940cba31f7f09b5aade56f9f6d7e45","first_computed_at":"2026-07-05T11:39:56.412892Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:56.412892Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fkWJqYCFu00yr6e2OaXla/81088C83KhdaFp52f7rjHH52iku4aWz2uV3ALjhpoJ7OYooaZqDadWpbmDL52CBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:56.414145Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.07854","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:965f12ae0a7eb1755280b11025209c1dd50577ed01d388abcc109415e399f312","sha256:8fb89a663780dfbfeb83e0c534b4b37380eaabe9bd7874c56a2ece19d4c59f12"],"state_sha256":"69de287e9ab04692592b2b45e88f7e544861b8c746d1be8198ba3ceb53f34fc6"}