{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JBBOINPIVTMN2SH4L2QXTDGXOA","short_pith_number":"pith:JBBOINPI","canonical_record":{"source":{"id":"2402.08480","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T14:13:17Z","cross_cats_sorted":["math.DG"],"title_canon_sha256":"ef23bcff34be9f5002ba1ada362023357067f972968fa7fa6fbc24bc1dee8666","abstract_canon_sha256":"ec6e738fc0b816d3bc6b0040dd8ba35b16fbb2f04453ca97f87693d6dc604bfe"},"schema_version":"1.0"},"canonical_sha256":"4842e435e8acd8dd48fc5ea1798cd770070d5c9129966481df25c690be12d636","source":{"kind":"arxiv","id":"2402.08480","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.08480","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"arxiv_version","alias_value":"2402.08480v1","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.08480","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"pith_short_12","alias_value":"JBBOINPIVTMN","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"pith_short_16","alias_value":"JBBOINPIVTMN2SH4","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"pith_short_8","alias_value":"JBBOINPI","created_at":"2026-07-05T07:44:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JBBOINPIVTMN2SH4L2QXTDGXOA","target":"record","payload":{"canonical_record":{"source":{"id":"2402.08480","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T14:13:17Z","cross_cats_sorted":["math.DG"],"title_canon_sha256":"ef23bcff34be9f5002ba1ada362023357067f972968fa7fa6fbc24bc1dee8666","abstract_canon_sha256":"ec6e738fc0b816d3bc6b0040dd8ba35b16fbb2f04453ca97f87693d6dc604bfe"},"schema_version":"1.0"},"canonical_sha256":"4842e435e8acd8dd48fc5ea1798cd770070d5c9129966481df25c690be12d636","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:44:47.316566Z","signature_b64":"k/ZHemehdx7u8xqW0kfvjAFusCPWabducw1ijw4nVVewVHxfn8lVHfuxAvqO6C1RNVopSM9Jo1lENshpXSI0DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4842e435e8acd8dd48fc5ea1798cd770070d5c9129966481df25c690be12d636","last_reissued_at":"2026-07-05T07:44:47.316049Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:44:47.316049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.08480","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":"2026-07-05T07:44:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g9+cp6gD9M5OQ3b+qrnvkYXczk8t0MQQyO8y45WV9vysy5DVgYexB0zUroqVHbz9Qknc8pqQpXCtMdx/g0R2AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T09:18:01.632356Z"},"content_sha256":"bca3f3cbfcabcc8c58bae42c4166c21ba0a7aa01e3c024b84e86ac00c44982bd","schema_version":"1.0","event_id":"sha256:bca3f3cbfcabcc8c58bae42c4166c21ba0a7aa01e3c024b84e86ac00c44982bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JBBOINPIVTMN2SH4L2QXTDGXOA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revealing Decurve Flows for Generalized Graph Propagation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["math.DG"],"primary_cat":"cs.LG","authors_text":"Chen Lin, Liheng Ma, Michael M. Bronstein, Philip H.S. Torr, Wanli Ouyang, Yiyang Chen","submitted_at":"2024-02-13T14:13:17Z","abstract_excerpt":"This study addresses the limitations of the traditional analysis of message-passing, central to graph learning, by defining {\\em \\textbf{generalized propagation}} with directed and weighted graphs. The significance manifest in two ways. \\textbf{Firstly}, we propose {\\em Generalized Propagation Neural Networks} (\\textbf{GPNNs}), a framework that unifies most propagation-based graph neural networks. By generating directed-weighted propagation graphs with adjacency function and connectivity function, GPNNs offer enhanced insights into attention mechanisms across various graph models. We delve int"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.08480","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/2402.08480/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":"2026-07-05T07:44:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6/1kLFMscZoLcIEPuSgmh6VOgzLjyViNPjPlYYo40OL9HyZ627DQ+SAYIYRUdsvFIXTsKctSw1SUNAztBI2mCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T09:18:01.632872Z"},"content_sha256":"cc0ce3cec6bf233030628c3872ab9c03f17ebfceb613713cf9ca2558adfec42c","schema_version":"1.0","event_id":"sha256:cc0ce3cec6bf233030628c3872ab9c03f17ebfceb613713cf9ca2558adfec42c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JBBOINPIVTMN2SH4L2QXTDGXOA/bundle.json","state_url":"https://pith.science/pith/JBBOINPIVTMN2SH4L2QXTDGXOA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JBBOINPIVTMN2SH4L2QXTDGXOA/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":"2026-08-07T09:18:01Z","links":{"resolver":"https://pith.science/pith/JBBOINPIVTMN2SH4L2QXTDGXOA","bundle":"https://pith.science/pith/JBBOINPIVTMN2SH4L2QXTDGXOA/bundle.json","state":"https://pith.science/pith/JBBOINPIVTMN2SH4L2QXTDGXOA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JBBOINPIVTMN2SH4L2QXTDGXOA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JBBOINPIVTMN2SH4L2QXTDGXOA","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":"ec6e738fc0b816d3bc6b0040dd8ba35b16fbb2f04453ca97f87693d6dc604bfe","cross_cats_sorted":["math.DG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T14:13:17Z","title_canon_sha256":"ef23bcff34be9f5002ba1ada362023357067f972968fa7fa6fbc24bc1dee8666"},"schema_version":"1.0","source":{"id":"2402.08480","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.08480","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"arxiv_version","alias_value":"2402.08480v1","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.08480","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"pith_short_12","alias_value":"JBBOINPIVTMN","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"pith_short_16","alias_value":"JBBOINPIVTMN2SH4","created_at":"2026-07-05T07:44:47Z"},{"alias_kind":"pith_short_8","alias_value":"JBBOINPI","created_at":"2026-07-05T07:44:47Z"}],"graph_snapshots":[{"event_id":"sha256:cc0ce3cec6bf233030628c3872ab9c03f17ebfceb613713cf9ca2558adfec42c","target":"graph","created_at":"2026-07-05T07:44:47Z","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/2402.08480/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study addresses the limitations of the traditional analysis of message-passing, central to graph learning, by defining {\\em \\textbf{generalized propagation}} with directed and weighted graphs. The significance manifest in two ways. \\textbf{Firstly}, we propose {\\em Generalized Propagation Neural Networks} (\\textbf{GPNNs}), a framework that unifies most propagation-based graph neural networks. By generating directed-weighted propagation graphs with adjacency function and connectivity function, GPNNs offer enhanced insights into attention mechanisms across various graph models. We delve int","authors_text":"Chen Lin, Liheng Ma, Michael M. Bronstein, Philip H.S. Torr, Wanli Ouyang, Yiyang Chen","cross_cats":["math.DG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T14:13:17Z","title":"Revealing Decurve Flows for Generalized Graph Propagation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.08480","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:bca3f3cbfcabcc8c58bae42c4166c21ba0a7aa01e3c024b84e86ac00c44982bd","target":"record","created_at":"2026-07-05T07:44:47Z","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":"ec6e738fc0b816d3bc6b0040dd8ba35b16fbb2f04453ca97f87693d6dc604bfe","cross_cats_sorted":["math.DG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T14:13:17Z","title_canon_sha256":"ef23bcff34be9f5002ba1ada362023357067f972968fa7fa6fbc24bc1dee8666"},"schema_version":"1.0","source":{"id":"2402.08480","kind":"arxiv","version":1}},"canonical_sha256":"4842e435e8acd8dd48fc5ea1798cd770070d5c9129966481df25c690be12d636","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4842e435e8acd8dd48fc5ea1798cd770070d5c9129966481df25c690be12d636","first_computed_at":"2026-07-05T07:44:47.316049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:44:47.316049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k/ZHemehdx7u8xqW0kfvjAFusCPWabducw1ijw4nVVewVHxfn8lVHfuxAvqO6C1RNVopSM9Jo1lENshpXSI0DA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:44:47.316566Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.08480","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bca3f3cbfcabcc8c58bae42c4166c21ba0a7aa01e3c024b84e86ac00c44982bd","sha256:cc0ce3cec6bf233030628c3872ab9c03f17ebfceb613713cf9ca2558adfec42c"],"state_sha256":"7ee6d9ceb235475581a1dc6823c331043feff4e9182619e4272bbc44c0c2609e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"63KxNIomaV5K/bwo+J/o+LdPyn3+M0qlRjiWjvNkJMNOa1UFHM7macGOQPJ+J6LjvwXk7vxIxh/daevuID9LCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T09:18:01.643260Z","bundle_sha256":"54b5805549e5bc0c5f8d11dad8ab0fd3fc821a4bc8fa632bc97dcadd5daeaf26"}}