{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FHDEJBFVCOCSSKGR2WHETT7BXE","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":"926eab33f7597c16eeed5d581c044f878ce0d1fd41afb28879771ced43acc888","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2018-12-21T06:56:50Z","title_canon_sha256":"b2e7c50993028e547fd91deab4a07dee7035c080e4d5aa596591256a53864ee7"},"schema_version":"1.0","source":{"id":"1812.08972","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.08972","created_at":"2026-05-17T23:57:45Z"},{"alias_kind":"arxiv_version","alias_value":"1812.08972v1","created_at":"2026-05-17T23:57:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.08972","created_at":"2026-05-17T23:57:45Z"},{"alias_kind":"pith_short_12","alias_value":"FHDEJBFVCOCS","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FHDEJBFVCOCSSKGR","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FHDEJBFV","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:8124d2bfd595f8f7a58ce227962168252c15089e5946a7a324e1fda41d26ace9","target":"graph","created_at":"2026-05-17T23:57:45Z","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"},"paper":{"abstract_excerpt":"There is recently a surge in approaches that learn low-dimensional embeddings of nodes in networks. As there are many large-scale real-world networks, it's inefficient for existing approaches to store amounts of parameters in memory and update them edge after edge. With the knowledge that nodes having similar neighborhood will be close to each other in embedding space, we propose COSINE (COmpresSIve NE) algorithm which reduces the memory footprint and accelerates the training process by parameters sharing among similar nodes. COSINE applies graph partitioning algorithms to networks and builds ","authors_text":"Bo Zhang, Cheng Yang, Leyu Lin, Maosong Sun, Zhengyan Zhang, Zhichong Fang, Zhiyuan Liu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2018-12-21T06:56:50Z","title":"COSINE: Compressive Network Embedding on Large-scale Information Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.08972","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":"sha256:47a728a67fff8089d392700479aae6de6bd27da5c8b33abe16be88f4e7a70bd6","target":"record","created_at":"2026-05-17T23:57:45Z","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":"926eab33f7597c16eeed5d581c044f878ce0d1fd41afb28879771ced43acc888","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2018-12-21T06:56:50Z","title_canon_sha256":"b2e7c50993028e547fd91deab4a07dee7035c080e4d5aa596591256a53864ee7"},"schema_version":"1.0","source":{"id":"1812.08972","kind":"arxiv","version":1}},"canonical_sha256":"29c64484b513852928d1d58e49cfe1b9088e5ac4ac61b9b2483fa00c28ed9621","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29c64484b513852928d1d58e49cfe1b9088e5ac4ac61b9b2483fa00c28ed9621","first_computed_at":"2026-05-17T23:57:45.748531Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:45.748531Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qEGm4T2aUjB3ArpAIX0vQ5oKID8J8TWXNEvIxFKLHjsVXi7EnG2AeWym1FeUMfiVb4COpeWs4cO48Wh8GkPdAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:45.748987Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.08972","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:47a728a67fff8089d392700479aae6de6bd27da5c8b33abe16be88f4e7a70bd6","sha256:8124d2bfd595f8f7a58ce227962168252c15089e5946a7a324e1fda41d26ace9"],"state_sha256":"8df5a759e1b9601bca0ca4a4efa48f0dfffaa4fb94a9ebf70b6c35e282f48939"}