{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:VPFROKJUCYFUUGBZF3L6CDNHLS","short_pith_number":"pith:VPFROKJU","canonical_record":{"source":{"id":"2412.01163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T06:05:10Z","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"title_canon_sha256":"ce9a6e395d5de5059109271245c2165c1e1bf60a0fe989d18d111fc1adffdf17","abstract_canon_sha256":"80055c6a9e24cb98027c2379d39d805dac301894818b97119b6d0ae999416515"},"schema_version":"1.0"},"canonical_sha256":"abcb172934160b4a18392ed7e10da75c8867b3e16d1b95ab7450813d57957a92","source":{"kind":"arxiv","id":"2412.01163","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.01163","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"arxiv_version","alias_value":"2412.01163v1","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01163","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"pith_short_12","alias_value":"VPFROKJUCYFU","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"pith_short_16","alias_value":"VPFROKJUCYFUUGBZ","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"pith_short_8","alias_value":"VPFROKJU","created_at":"2026-07-05T09:42:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:VPFROKJUCYFUUGBZF3L6CDNHLS","target":"record","payload":{"canonical_record":{"source":{"id":"2412.01163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T06:05:10Z","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"title_canon_sha256":"ce9a6e395d5de5059109271245c2165c1e1bf60a0fe989d18d111fc1adffdf17","abstract_canon_sha256":"80055c6a9e24cb98027c2379d39d805dac301894818b97119b6d0ae999416515"},"schema_version":"1.0"},"canonical_sha256":"abcb172934160b4a18392ed7e10da75c8867b3e16d1b95ab7450813d57957a92","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:42:55.128486Z","signature_b64":"D8nyILPeksEXb5OAhotRRkQJky6i6gyk3buScFxFl8rg2QoFDL8WYBDpRRlRvnAB3HKkE3jlnLpxf5PLFOM6BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"abcb172934160b4a18392ed7e10da75c8867b3e16d1b95ab7450813d57957a92","last_reissued_at":"2026-07-05T09:42:55.127992Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:42:55.127992Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.01163","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":"2026-07-05T09:42:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/dbaAoLG8LSydWJkN8gpA9fswQsaEo1px2Be0kDkJgZl10CvQC764EulTged94mhiYRsswdBwPD12JecUPDgBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:17:56.008622Z"},"content_sha256":"4729e1ad958bf6d985c1fd70f324b8c42363cfc23b8b259e94a79d331d395a50","schema_version":"1.0","event_id":"sha256:4729e1ad958bf6d985c1fd70f324b8c42363cfc23b8b259e94a79d331d395a50"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:VPFROKJUCYFUUGBZF3L6CDNHLS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph Community Augmentation with GMM-based Modeling in Latent Space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","math.IT","stat.ML"],"primary_cat":"cs.LG","authors_text":"Kenji Yamanishi, Shintaro Fukushima","submitted_at":"2024-12-02T06:05:10Z","abstract_excerpt":"This study addresses the issue of graph generation with generative models. In particular, we are concerned with graph community augmentation problem, which refers to the problem of generating unseen or unfamiliar graphs with a new community out of the probability distribution estimated with a given graph dataset. The graph community augmentation means that the generated graphs have a new community. There is a chance of discovering an unseen but important structure of graphs with a new community, for example, in a social network such as a purchaser network. Graph community augmentation may also"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01163","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/2412.01163/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":"2026-07-05T09:42:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mi5dCQFpd1GdCG2dLN/FIle0EeOeCyyf1Qwu8VKvPG5MNsFqK1IJJuRjgfFe9IwLAqMUE3gPFb8/7eucbv3pBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:17:56.009161Z"},"content_sha256":"3506856018a2e4a9b9a0d2f7c23ec64050d1d2f106a426fc7e701a3d93d3165c","schema_version":"1.0","event_id":"sha256:3506856018a2e4a9b9a0d2f7c23ec64050d1d2f106a426fc7e701a3d93d3165c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VPFROKJUCYFUUGBZF3L6CDNHLS/bundle.json","state_url":"https://pith.science/pith/VPFROKJUCYFUUGBZF3L6CDNHLS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VPFROKJUCYFUUGBZF3L6CDNHLS/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":"2026-08-19T03:17:56Z","links":{"resolver":"https://pith.science/pith/VPFROKJUCYFUUGBZF3L6CDNHLS","bundle":"https://pith.science/pith/VPFROKJUCYFUUGBZF3L6CDNHLS/bundle.json","state":"https://pith.science/pith/VPFROKJUCYFUUGBZF3L6CDNHLS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VPFROKJUCYFUUGBZF3L6CDNHLS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:VPFROKJUCYFUUGBZF3L6CDNHLS","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":"80055c6a9e24cb98027c2379d39d805dac301894818b97119b6d0ae999416515","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T06:05:10Z","title_canon_sha256":"ce9a6e395d5de5059109271245c2165c1e1bf60a0fe989d18d111fc1adffdf17"},"schema_version":"1.0","source":{"id":"2412.01163","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.01163","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"arxiv_version","alias_value":"2412.01163v1","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01163","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"pith_short_12","alias_value":"VPFROKJUCYFU","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"pith_short_16","alias_value":"VPFROKJUCYFUUGBZ","created_at":"2026-07-05T09:42:55Z"},{"alias_kind":"pith_short_8","alias_value":"VPFROKJU","created_at":"2026-07-05T09:42:55Z"}],"graph_snapshots":[{"event_id":"sha256:3506856018a2e4a9b9a0d2f7c23ec64050d1d2f106a426fc7e701a3d93d3165c","target":"graph","created_at":"2026-07-05T09:42:55Z","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/2412.01163/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study addresses the issue of graph generation with generative models. In particular, we are concerned with graph community augmentation problem, which refers to the problem of generating unseen or unfamiliar graphs with a new community out of the probability distribution estimated with a given graph dataset. The graph community augmentation means that the generated graphs have a new community. There is a chance of discovering an unseen but important structure of graphs with a new community, for example, in a social network such as a purchaser network. Graph community augmentation may also","authors_text":"Kenji Yamanishi, Shintaro Fukushima","cross_cats":["cs.IT","math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T06:05:10Z","title":"Graph Community Augmentation with GMM-based Modeling in Latent Space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01163","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":"sha256:4729e1ad958bf6d985c1fd70f324b8c42363cfc23b8b259e94a79d331d395a50","target":"record","created_at":"2026-07-05T09:42:55Z","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":"80055c6a9e24cb98027c2379d39d805dac301894818b97119b6d0ae999416515","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-02T06:05:10Z","title_canon_sha256":"ce9a6e395d5de5059109271245c2165c1e1bf60a0fe989d18d111fc1adffdf17"},"schema_version":"1.0","source":{"id":"2412.01163","kind":"arxiv","version":1}},"canonical_sha256":"abcb172934160b4a18392ed7e10da75c8867b3e16d1b95ab7450813d57957a92","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"abcb172934160b4a18392ed7e10da75c8867b3e16d1b95ab7450813d57957a92","first_computed_at":"2026-07-05T09:42:55.127992Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:42:55.127992Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D8nyILPeksEXb5OAhotRRkQJky6i6gyk3buScFxFl8rg2QoFDL8WYBDpRRlRvnAB3HKkE3jlnLpxf5PLFOM6BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:42:55.128486Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.01163","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4729e1ad958bf6d985c1fd70f324b8c42363cfc23b8b259e94a79d331d395a50","sha256:3506856018a2e4a9b9a0d2f7c23ec64050d1d2f106a426fc7e701a3d93d3165c"],"state_sha256":"527562919cd12843fa9e05aad2aa72642dc9ad933a7c68228b82777328a630bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DqLFM7c9g/U/UkH3MmUQFti7hvM0muMFy1UfJ3EjjCR1kqQpZeVBod4aUSintTYjJLzpRlmgFpUe8ufWMYa9DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T03:17:56.013622Z","bundle_sha256":"077cb884cd2bb02bf162a1ec4ee0c28a09ba0c229764a220b3dac565a1a56ed2"}}