{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:B76JOX7XXX6EETPA6L5OCBDWMZ","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":"b72cbbf1b9ea84690dafe1e485122a01261831cc9541193a9f778d7eda1c9303","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-20T09:45:57Z","title_canon_sha256":"64ff9f90e99995b3187930aae0e0ced62bb46600b219b8175dea2e746766986b"},"schema_version":"1.0","source":{"id":"2205.10053","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.10053","created_at":"2026-07-05T06:14:34Z"},{"alias_kind":"arxiv_version","alias_value":"2205.10053v2","created_at":"2026-07-05T06:14:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.10053","created_at":"2026-07-05T06:14:34Z"},{"alias_kind":"pith_short_12","alias_value":"B76JOX7XXX6E","created_at":"2026-07-05T06:14:34Z"},{"alias_kind":"pith_short_16","alias_value":"B76JOX7XXX6EETPA","created_at":"2026-07-05T06:14:34Z"},{"alias_kind":"pith_short_8","alias_value":"B76JOX7X","created_at":"2026-07-05T06:14:34Z"}],"graph_snapshots":[{"event_id":"sha256:79eb84ecef8ad663bc02bb20a8e6790c209d88e6e21845013af2a3a9cdf45a74","target":"graph","created_at":"2026-07-05T06:14:34Z","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/2205.10053/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The last years have witnessed the emergence of a promising self-supervised learning strategy, referred to as masked autoencoding. However, there is a lack of theoretical understanding of how masking matters on graph autoencoders (GAEs). In this work, we present masked graph autoencoder (MaskGAE), a self-supervised learning framework for graph-structured data. Different from standard GAEs, MaskGAE adopts masked graph modeling (MGM) as a principled pretext task - masking a portion of edges and attempting to reconstruct the missing part with partially visible, unmasked graph structure. To underst","authors_text":"Changhua Meng, Jintang Li, Liang Chen, Liang Zhu, Ruofan Wu, Sheng Tian, Wangbin Sun, Weiqiang Wang, Zibin Zheng","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-20T09:45:57Z","title":"What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.10053","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:d0b6b604ce0af586cbb66ed527356442ac4b9dfb98aeb31a876d6c4707a7a569","target":"record","created_at":"2026-07-05T06:14:34Z","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":"b72cbbf1b9ea84690dafe1e485122a01261831cc9541193a9f778d7eda1c9303","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-20T09:45:57Z","title_canon_sha256":"64ff9f90e99995b3187930aae0e0ced62bb46600b219b8175dea2e746766986b"},"schema_version":"1.0","source":{"id":"2205.10053","kind":"arxiv","version":2}},"canonical_sha256":"0ffc975ff7bdfc424de0f2fae10476667aea293401ce45e68da53e93856da55d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0ffc975ff7bdfc424de0f2fae10476667aea293401ce45e68da53e93856da55d","first_computed_at":"2026-07-05T06:14:34.784781Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:14:34.784781Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iRlCvcSjfqjphHE9BKUo7zoxkKik4ltCuikAMaFtfB+GIj7nL5wq+j4mTdZaqKEZa6U6R2ug7ZhZf9ODZzH6Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:14:34.785334Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.10053","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0b6b604ce0af586cbb66ed527356442ac4b9dfb98aeb31a876d6c4707a7a569","sha256:79eb84ecef8ad663bc02bb20a8e6790c209d88e6e21845013af2a3a9cdf45a74"],"state_sha256":"a32b4ba7c73e1c8aee0ba3646312289527b4425648cd2146335f96c818a008b4"}