{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:3WUORBBVPZM3T7BM4QPGPAWX5N","short_pith_number":"pith:3WUORBBV","canonical_record":{"source":{"id":"2211.10794","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-19T20:43:39Z","cross_cats_sorted":[],"title_canon_sha256":"3af73d2ac47227299cb8be7533cf6725d4bb5b54e4dd50f9d9161739e351037b","abstract_canon_sha256":"f506037baa64d888e9efe999466a56ed1362445d4b01095d8821a39549741e82"},"schema_version":"1.0"},"canonical_sha256":"dda8e884357e59b9fc2ce41e6782d7eb43e725c8a18ee15a3b689ef0acb2840c","source":{"kind":"arxiv","id":"2211.10794","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.10794","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"arxiv_version","alias_value":"2211.10794v2","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.10794","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"pith_short_12","alias_value":"3WUORBBVPZM3","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"pith_short_16","alias_value":"3WUORBBVPZM3T7BM","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"pith_short_8","alias_value":"3WUORBBV","created_at":"2026-07-05T06:21:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:3WUORBBVPZM3T7BM4QPGPAWX5N","target":"record","payload":{"canonical_record":{"source":{"id":"2211.10794","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-19T20:43:39Z","cross_cats_sorted":[],"title_canon_sha256":"3af73d2ac47227299cb8be7533cf6725d4bb5b54e4dd50f9d9161739e351037b","abstract_canon_sha256":"f506037baa64d888e9efe999466a56ed1362445d4b01095d8821a39549741e82"},"schema_version":"1.0"},"canonical_sha256":"dda8e884357e59b9fc2ce41e6782d7eb43e725c8a18ee15a3b689ef0acb2840c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:21:55.539308Z","signature_b64":"/TiAwxgwB/x3wEsG9amacF97aEJcozZlt6FocrL8t/e6HIt1yhh7YMugwj2NLxC8+1klb622/alKM4Xuv9CKAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dda8e884357e59b9fc2ce41e6782d7eb43e725c8a18ee15a3b689ef0acb2840c","last_reissued_at":"2026-07-05T06:21:55.538853Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:21:55.538853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.10794","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:21:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KzILWXI9hgZLTi6OxHysoRFMrai9Z1g4+rLgky2E4jr9dO1oq+fWFz8JXjRlr/CuIMbFbPDXMwPn5EjG7dtKAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T05:22:37.296150Z"},"content_sha256":"d95e8b383fdfb773163815668a93dd88fafc0d241cf6c86fb381247ea839b734","schema_version":"1.0","event_id":"sha256:d95e8b383fdfb773163815668a93dd88fafc0d241cf6c86fb381247ea839b734"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:3WUORBBVPZM3T7BM4QPGPAWX5N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NVDiff: Graph Generation through the Diffusion of Node Vectors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Aonan Zhang, Li-Ping Liu, Xiaohui Chen, Yukun Li","submitted_at":"2022-11-19T20:43:39Z","abstract_excerpt":"Learning to generate graphs is challenging as a graph is a set of pairwise connected, unordered nodes encoding complex combinatorial structures. Recently, several works have proposed graph generative models based on normalizing flows or score-based diffusion models. However, these models need to generate nodes and edges in parallel from the same process, whose dimensionality is unnecessarily high. We propose NVDiff, which takes the VGAE structure and uses a score-based generative model (SGM) as a flexible prior to sample node vectors. By modeling only node vectors in the latent space, NVDiff s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.10794","kind":"arxiv","version":2},"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/2211.10794/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":"2026-07-05T06:21:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GI2oCLgbt4J0NUqc4Pws7uVCVWXxAhye43E5qhtnY3buLIV9G8/055ldMHmINNPL3a0Uc6Sxk+coQlQAgyTjCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T05:22:37.296648Z"},"content_sha256":"4b0c6ec921227139ea31d0e5d35d9c4b571982c3863bb0056c84b9c4cda83a3a","schema_version":"1.0","event_id":"sha256:4b0c6ec921227139ea31d0e5d35d9c4b571982c3863bb0056c84b9c4cda83a3a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3WUORBBVPZM3T7BM4QPGPAWX5N/bundle.json","state_url":"https://pith.science/pith/3WUORBBVPZM3T7BM4QPGPAWX5N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3WUORBBVPZM3T7BM4QPGPAWX5N/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":"2026-08-21T05:22:37Z","links":{"resolver":"https://pith.science/pith/3WUORBBVPZM3T7BM4QPGPAWX5N","bundle":"https://pith.science/pith/3WUORBBVPZM3T7BM4QPGPAWX5N/bundle.json","state":"https://pith.science/pith/3WUORBBVPZM3T7BM4QPGPAWX5N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3WUORBBVPZM3T7BM4QPGPAWX5N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:3WUORBBVPZM3T7BM4QPGPAWX5N","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":"f506037baa64d888e9efe999466a56ed1362445d4b01095d8821a39549741e82","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-19T20:43:39Z","title_canon_sha256":"3af73d2ac47227299cb8be7533cf6725d4bb5b54e4dd50f9d9161739e351037b"},"schema_version":"1.0","source":{"id":"2211.10794","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.10794","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"arxiv_version","alias_value":"2211.10794v2","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.10794","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"pith_short_12","alias_value":"3WUORBBVPZM3","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"pith_short_16","alias_value":"3WUORBBVPZM3T7BM","created_at":"2026-07-05T06:21:55Z"},{"alias_kind":"pith_short_8","alias_value":"3WUORBBV","created_at":"2026-07-05T06:21:55Z"}],"graph_snapshots":[{"event_id":"sha256:4b0c6ec921227139ea31d0e5d35d9c4b571982c3863bb0056c84b9c4cda83a3a","target":"graph","created_at":"2026-07-05T06:21:55Z","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/2211.10794/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning to generate graphs is challenging as a graph is a set of pairwise connected, unordered nodes encoding complex combinatorial structures. Recently, several works have proposed graph generative models based on normalizing flows or score-based diffusion models. However, these models need to generate nodes and edges in parallel from the same process, whose dimensionality is unnecessarily high. We propose NVDiff, which takes the VGAE structure and uses a score-based generative model (SGM) as a flexible prior to sample node vectors. By modeling only node vectors in the latent space, NVDiff s","authors_text":"Aonan Zhang, Li-Ping Liu, Xiaohui Chen, Yukun Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-19T20:43:39Z","title":"NVDiff: Graph Generation through the Diffusion of Node Vectors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.10794","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:d95e8b383fdfb773163815668a93dd88fafc0d241cf6c86fb381247ea839b734","target":"record","created_at":"2026-07-05T06:21:55Z","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":"f506037baa64d888e9efe999466a56ed1362445d4b01095d8821a39549741e82","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-19T20:43:39Z","title_canon_sha256":"3af73d2ac47227299cb8be7533cf6725d4bb5b54e4dd50f9d9161739e351037b"},"schema_version":"1.0","source":{"id":"2211.10794","kind":"arxiv","version":2}},"canonical_sha256":"dda8e884357e59b9fc2ce41e6782d7eb43e725c8a18ee15a3b689ef0acb2840c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dda8e884357e59b9fc2ce41e6782d7eb43e725c8a18ee15a3b689ef0acb2840c","first_computed_at":"2026-07-05T06:21:55.538853Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:21:55.538853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/TiAwxgwB/x3wEsG9amacF97aEJcozZlt6FocrL8t/e6HIt1yhh7YMugwj2NLxC8+1klb622/alKM4Xuv9CKAw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:21:55.539308Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.10794","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d95e8b383fdfb773163815668a93dd88fafc0d241cf6c86fb381247ea839b734","sha256:4b0c6ec921227139ea31d0e5d35d9c4b571982c3863bb0056c84b9c4cda83a3a"],"state_sha256":"2a48563035fb95c5bfd661ff32d8c062171462c255670307a8b1178155676b67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o+METpmtQnCrISQVCnndgjip9VvRHOiQu+5xmEaNc3lF4wEKeSHbcYCDe0TCgmYsDfBB5P/4gTywGh6UgDh1Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T05:22:37.300558Z","bundle_sha256":"0fdd744c3c7cc394f94d75a6686e052dd505d153e4f3ef56d1bb3a55e90892a2"}}