{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OW2YZRGO2IR4Q6WJDKJLVELSGV","short_pith_number":"pith:OW2YZRGO","canonical_record":{"source":{"id":"2401.12007","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-22T14:55:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e50a872564dac7eed8fc644bad37a2ef9ac93a08dc3f7b2f37e87b04e583cf2f","abstract_canon_sha256":"585080005b3b57afadd44a0645904de938ef990f573303e70124646ebbd04f27"},"schema_version":"1.0"},"canonical_sha256":"75b58cc4ced223c87ac91a92ba9172355321ec42b3754fee98e5ece2ff5be824","source":{"kind":"arxiv","id":"2401.12007","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.12007","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"arxiv_version","alias_value":"2401.12007v3","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.12007","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"pith_short_12","alias_value":"OW2YZRGO2IR4","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"pith_short_16","alias_value":"OW2YZRGO2IR4Q6WJ","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"pith_short_8","alias_value":"OW2YZRGO","created_at":"2026-07-05T07:38:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OW2YZRGO2IR4Q6WJDKJLVELSGV","target":"record","payload":{"canonical_record":{"source":{"id":"2401.12007","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-22T14:55:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e50a872564dac7eed8fc644bad37a2ef9ac93a08dc3f7b2f37e87b04e583cf2f","abstract_canon_sha256":"585080005b3b57afadd44a0645904de938ef990f573303e70124646ebbd04f27"},"schema_version":"1.0"},"canonical_sha256":"75b58cc4ced223c87ac91a92ba9172355321ec42b3754fee98e5ece2ff5be824","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:38:54.228024Z","signature_b64":"HA+EjLy1EMhcwCBIubXhkm+D3pkD532xXNXiQvsjO6QUexfrOJOyHtQEfuSXAG0+SlXV4PVIZZuEHnTWb1M1BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75b58cc4ced223c87ac91a92ba9172355321ec42b3754fee98e5ece2ff5be824","last_reissued_at":"2026-07-05T07:38:54.227452Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:38:54.227452Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.12007","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:38:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6ivyQR50dCsxEYOtYTkmjPRGGFnOyXMMPJdpd5xNKlYazD/LNtle/q0OBAEmxfqKJmBtUpXe8Vk/J+pbiFooCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T04:17:08.966506Z"},"content_sha256":"90e3ba95a4563b67eeb5cc615c494b5a0c1714e9bee53cbcdd6f62e20d6931b8","schema_version":"1.0","event_id":"sha256:90e3ba95a4563b67eeb5cc615c494b5a0c1714e9bee53cbcdd6f62e20d6931b8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OW2YZRGO2IR4Q6WJDKJLVELSGV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tensor-view Topological Graph Neural Network","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Elynn Chen, Tao Wen, Yuzhou Chen","submitted_at":"2024-01-22T14:55:01Z","abstract_excerpt":"Graph classification is an important learning task for graph-structured data. Graph neural networks (GNNs) have recently gained growing attention in graph learning and have shown significant improvements in many important graph problems. Despite their state-of-the-art performances, existing GNNs only use local information from a very limited neighborhood around each node, suffering from loss of multi-modal information and overheads of excessive computation. To address these issues, we propose a novel Tensor-view Topological Graph Neural Network (TTG-NN), a class of simple yet effective topolog"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.12007","kind":"arxiv","version":3},"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/2401.12007/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":"2026-07-05T07:38:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6HKUbCD97v/R6PBuczxXJkCdlb9aiVV3xmWRcEaevmNO2HK8+mpaJVgbY9NNEoXeEsYIFZ9kQouIl6IfQiTSCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T04:17:08.966881Z"},"content_sha256":"c5c580d631da97c3de04a84fd50fb70fd74f6d3a4f12476951f46eb91f0c96d6","schema_version":"1.0","event_id":"sha256:c5c580d631da97c3de04a84fd50fb70fd74f6d3a4f12476951f46eb91f0c96d6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV/bundle.json","state_url":"https://pith.science/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV/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":"2026-07-17T04:17:08Z","links":{"resolver":"https://pith.science/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV","bundle":"https://pith.science/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV/bundle.json","state":"https://pith.science/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OW2YZRGO2IR4Q6WJDKJLVELSGV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OW2YZRGO2IR4Q6WJDKJLVELSGV","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":"585080005b3b57afadd44a0645904de938ef990f573303e70124646ebbd04f27","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-22T14:55:01Z","title_canon_sha256":"e50a872564dac7eed8fc644bad37a2ef9ac93a08dc3f7b2f37e87b04e583cf2f"},"schema_version":"1.0","source":{"id":"2401.12007","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.12007","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"arxiv_version","alias_value":"2401.12007v3","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.12007","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"pith_short_12","alias_value":"OW2YZRGO2IR4","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"pith_short_16","alias_value":"OW2YZRGO2IR4Q6WJ","created_at":"2026-07-05T07:38:54Z"},{"alias_kind":"pith_short_8","alias_value":"OW2YZRGO","created_at":"2026-07-05T07:38:54Z"}],"graph_snapshots":[{"event_id":"sha256:c5c580d631da97c3de04a84fd50fb70fd74f6d3a4f12476951f46eb91f0c96d6","target":"graph","created_at":"2026-07-05T07:38:54Z","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/2401.12007/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph classification is an important learning task for graph-structured data. Graph neural networks (GNNs) have recently gained growing attention in graph learning and have shown significant improvements in many important graph problems. Despite their state-of-the-art performances, existing GNNs only use local information from a very limited neighborhood around each node, suffering from loss of multi-modal information and overheads of excessive computation. To address these issues, we propose a novel Tensor-view Topological Graph Neural Network (TTG-NN), a class of simple yet effective topolog","authors_text":"Elynn Chen, Tao Wen, Yuzhou Chen","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-22T14:55:01Z","title":"Tensor-view Topological Graph Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.12007","kind":"arxiv","version":3},"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":"sha256:90e3ba95a4563b67eeb5cc615c494b5a0c1714e9bee53cbcdd6f62e20d6931b8","target":"record","created_at":"2026-07-05T07:38:54Z","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":"585080005b3b57afadd44a0645904de938ef990f573303e70124646ebbd04f27","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-22T14:55:01Z","title_canon_sha256":"e50a872564dac7eed8fc644bad37a2ef9ac93a08dc3f7b2f37e87b04e583cf2f"},"schema_version":"1.0","source":{"id":"2401.12007","kind":"arxiv","version":3}},"canonical_sha256":"75b58cc4ced223c87ac91a92ba9172355321ec42b3754fee98e5ece2ff5be824","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75b58cc4ced223c87ac91a92ba9172355321ec42b3754fee98e5ece2ff5be824","first_computed_at":"2026-07-05T07:38:54.227452Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:38:54.227452Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HA+EjLy1EMhcwCBIubXhkm+D3pkD532xXNXiQvsjO6QUexfrOJOyHtQEfuSXAG0+SlXV4PVIZZuEHnTWb1M1BA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:38:54.228024Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.12007","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90e3ba95a4563b67eeb5cc615c494b5a0c1714e9bee53cbcdd6f62e20d6931b8","sha256:c5c580d631da97c3de04a84fd50fb70fd74f6d3a4f12476951f46eb91f0c96d6"],"state_sha256":"a7e8f481ef2623988824f6ffff3295fa1fc324c21c44ccd821809502daefd3e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qfQ3a0amm1XT8mXowE8wqkxwf2iLTQH0EWWbgnNGL6k3aeyONTOJL9lyl7smyWwnWhoXbPlwvwVmWvp9MeQ/Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-17T04:17:08.968994Z","bundle_sha256":"5734a6e07ab4d7d04a4ac076160352c87edc380997f2acb3c24608b0c919d805"}}