{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZM4MXKDSHLG2D46DO4OWAMRQA6","short_pith_number":"pith:ZM4MXKDS","canonical_record":{"source":{"id":"2407.11615","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-16T11:24:28Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2060c06b9d848d1e3a353e92c0df99329c70f35ac40b59e30491667a7fa7314a","abstract_canon_sha256":"b6e18a71c0661ddef1f8da6b2dd018eafff492bb8fc8430d8941557e85449029"},"schema_version":"1.0"},"canonical_sha256":"cb38cba8723acda1f3c3771d6032300781ded7f149f0293f87cd0fe6328e4675","source":{"kind":"arxiv","id":"2407.11615","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.11615","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"arxiv_version","alias_value":"2407.11615v1","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.11615","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"pith_short_12","alias_value":"ZM4MXKDSHLG2","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"pith_short_16","alias_value":"ZM4MXKDSHLG2D46D","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"pith_short_8","alias_value":"ZM4MXKDS","created_at":"2026-07-05T08:44:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZM4MXKDSHLG2D46DO4OWAMRQA6","target":"record","payload":{"canonical_record":{"source":{"id":"2407.11615","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-16T11:24:28Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2060c06b9d848d1e3a353e92c0df99329c70f35ac40b59e30491667a7fa7314a","abstract_canon_sha256":"b6e18a71c0661ddef1f8da6b2dd018eafff492bb8fc8430d8941557e85449029"},"schema_version":"1.0"},"canonical_sha256":"cb38cba8723acda1f3c3771d6032300781ded7f149f0293f87cd0fe6328e4675","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:44:26.957233Z","signature_b64":"uwgkkuqaedSRHUI71TRPT7beSsjFZrkRVmVb2aF+IWSvcco6ocKBrxnd9s6ik3I8tOwXA1FGhwhW/EwuRKVfAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb38cba8723acda1f3c3771d6032300781ded7f149f0293f87cd0fe6328e4675","last_reissued_at":"2026-07-05T08:44:26.956879Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:44:26.956879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.11615","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:44:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G/YFXFlUsKgs6PWuxBpmsxyGWdKS5hxjSA0icC9SKYi6DtdpTji6P/OHceqrw/PQmmR2zU0reZO6nquaSOUMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:12:23.190070Z"},"content_sha256":"858e3013ba8ec45c3cc3caaf68c73de1f9d897397d2e43520e9c1009ed81b6e7","schema_version":"1.0","event_id":"sha256:858e3013ba8ec45c3cc3caaf68c73de1f9d897397d2e43520e9c1009ed81b6e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZM4MXKDSHLG2D46DO4OWAMRQA6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph Dimension Attention Networks for Enterprise Credit Assessment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Beni Egressy, Fuzhen Zhuang, Gang Kou, Roger Wattenhofer, Shaopeng Wei, Xingyan Chen, Yu Zhao","submitted_at":"2024-07-16T11:24:28Z","abstract_excerpt":"Enterprise credit assessment is critical for evaluating financial risk, and Graph Neural Networks (GNNs), with their advanced capability to model inter-entity relationships, are a natural tool to get a deeper understanding of these financial networks. However, existing GNN-based methodologies predominantly emphasize entity-level attention mechanisms for contagion risk aggregation, often overlooking the heterogeneous importance of different feature dimensions, thus falling short in adequately modeling credit risk levels. To address this issue, we propose a novel architecture named Graph Dimensi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.11615","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/2407.11615/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:44:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kAwY0QQFPfjCV2yzGJMLPILKO11u1LlNEnKJc7NJwa4i2BC3WEhwAzKQlo9jAihoX040bJSH2MExdOSTh0zEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:12:23.190465Z"},"content_sha256":"10876bf0537a4aada60e391796f50d902c1846973ae36681c4546cecf6dd87f7","schema_version":"1.0","event_id":"sha256:10876bf0537a4aada60e391796f50d902c1846973ae36681c4546cecf6dd87f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6/bundle.json","state_url":"https://pith.science/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-08T19:12:23Z","links":{"resolver":"https://pith.science/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6","bundle":"https://pith.science/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6/bundle.json","state":"https://pith.science/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZM4MXKDSHLG2D46DO4OWAMRQA6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZM4MXKDSHLG2D46DO4OWAMRQA6","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":"b6e18a71c0661ddef1f8da6b2dd018eafff492bb8fc8430d8941557e85449029","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-16T11:24:28Z","title_canon_sha256":"2060c06b9d848d1e3a353e92c0df99329c70f35ac40b59e30491667a7fa7314a"},"schema_version":"1.0","source":{"id":"2407.11615","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.11615","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"arxiv_version","alias_value":"2407.11615v1","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.11615","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"pith_short_12","alias_value":"ZM4MXKDSHLG2","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"pith_short_16","alias_value":"ZM4MXKDSHLG2D46D","created_at":"2026-07-05T08:44:26Z"},{"alias_kind":"pith_short_8","alias_value":"ZM4MXKDS","created_at":"2026-07-05T08:44:26Z"}],"graph_snapshots":[{"event_id":"sha256:10876bf0537a4aada60e391796f50d902c1846973ae36681c4546cecf6dd87f7","target":"graph","created_at":"2026-07-05T08:44:26Z","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/2407.11615/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Enterprise credit assessment is critical for evaluating financial risk, and Graph Neural Networks (GNNs), with their advanced capability to model inter-entity relationships, are a natural tool to get a deeper understanding of these financial networks. However, existing GNN-based methodologies predominantly emphasize entity-level attention mechanisms for contagion risk aggregation, often overlooking the heterogeneous importance of different feature dimensions, thus falling short in adequately modeling credit risk levels. To address this issue, we propose a novel architecture named Graph Dimensi","authors_text":"Beni Egressy, Fuzhen Zhuang, Gang Kou, Roger Wattenhofer, Shaopeng Wei, Xingyan Chen, Yu Zhao","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-16T11:24:28Z","title":"Graph Dimension Attention Networks for Enterprise Credit Assessment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.11615","kind":"arxiv","version":1},"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":"sha256:858e3013ba8ec45c3cc3caaf68c73de1f9d897397d2e43520e9c1009ed81b6e7","target":"record","created_at":"2026-07-05T08:44:26Z","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":"b6e18a71c0661ddef1f8da6b2dd018eafff492bb8fc8430d8941557e85449029","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-16T11:24:28Z","title_canon_sha256":"2060c06b9d848d1e3a353e92c0df99329c70f35ac40b59e30491667a7fa7314a"},"schema_version":"1.0","source":{"id":"2407.11615","kind":"arxiv","version":1}},"canonical_sha256":"cb38cba8723acda1f3c3771d6032300781ded7f149f0293f87cd0fe6328e4675","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb38cba8723acda1f3c3771d6032300781ded7f149f0293f87cd0fe6328e4675","first_computed_at":"2026-07-05T08:44:26.956879Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:44:26.956879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uwgkkuqaedSRHUI71TRPT7beSsjFZrkRVmVb2aF+IWSvcco6ocKBrxnd9s6ik3I8tOwXA1FGhwhW/EwuRKVfAg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:44:26.957233Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.11615","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:858e3013ba8ec45c3cc3caaf68c73de1f9d897397d2e43520e9c1009ed81b6e7","sha256:10876bf0537a4aada60e391796f50d902c1846973ae36681c4546cecf6dd87f7"],"state_sha256":"3ac174f541dc388d87ae9494764003778e3780d3bc56f48bd1118f45640a1bd7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ODXN+XiIjxppgGuXHVkq4zAyqGrpBCssUIPiYiTg66wvFgjyxfCAbDRT50y76la9boISnBklOxDjvBcbIeIXDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T19:12:23.192477Z","bundle_sha256":"c6fc0c13e66ce00656f49b5a1d5e89f892b343ebc11c8fce12bf9dbc9d159122"}}