{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CM5AKZUWNIQ2XJTTXSRBPTLRMB","short_pith_number":"pith:CM5AKZUW","canonical_record":{"source":{"id":"1802.09612","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-26T21:18:43Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"b5c046bbd6ab1bbbba5e5032adf08954c568e5f86be25f9bad3cba9f76df4845","abstract_canon_sha256":"b5de55a384b1d293d22085c03b06733cab8d237efdbdb99852fe027ee2cf16dc"},"schema_version":"1.0"},"canonical_sha256":"133a0566966a21aba673bca217cd716070b21b49ee895f306d8659bea136be78","source":{"kind":"arxiv","id":"1802.09612","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.09612","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"arxiv_version","alias_value":"1802.09612v2","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.09612","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"pith_short_12","alias_value":"CM5AKZUWNIQ2","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"pith_short_16","alias_value":"CM5AKZUWNIQ2XJTT","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"pith_short_8","alias_value":"CM5AKZUW","created_at":"2026-07-05T01:27:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CM5AKZUWNIQ2XJTTXSRBPTLRMB","target":"record","payload":{"canonical_record":{"source":{"id":"1802.09612","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-26T21:18:43Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"b5c046bbd6ab1bbbba5e5032adf08954c568e5f86be25f9bad3cba9f76df4845","abstract_canon_sha256":"b5de55a384b1d293d22085c03b06733cab8d237efdbdb99852fe027ee2cf16dc"},"schema_version":"1.0"},"canonical_sha256":"133a0566966a21aba673bca217cd716070b21b49ee895f306d8659bea136be78","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:00.205621Z","signature_b64":"MJwz5XvyzNcRUeXelduETllh4szPvxWC+kLMPgCbYAFqE1npsMHEavdscx+pVzcUEGGVOFhi2ptBrL7US+FABw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"133a0566966a21aba673bca217cd716070b21b49ee895f306d8659bea136be78","last_reissued_at":"2026-07-05T01:27:00.205134Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:00.205134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.09612","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":"2026-07-05T01:27:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Irg64hOXkncyA4yMy6hbBmJZbHmSS3g4IIvCv6QgFD3hv89orplQHvFpwwTwetF8Sg2pfk6pZckq2rnB0lu9BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T04:11:42.355990Z"},"content_sha256":"ba60333033b53ca836789134824afb50f46315b126f435abde6c63e00f576ab8","schema_version":"1.0","event_id":"sha256:ba60333033b53ca836789134824afb50f46315b126f435abde6c63e00f576ab8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CM5AKZUWNIQ2XJTTXSRBPTLRMB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MILE: A Multi-Level Framework for Scalable Graph Embedding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.AI","authors_text":"Jiongqian Liang, Saket Gurukar, Srinivasan Parthasarathy","submitted_at":"2018-02-26T21:18:43Z","abstract_excerpt":"Recently there has been a surge of interest in designing graph embedding methods. Few, if any, can scale to a large-sized graph with millions of nodes due to both computational complexity and memory requirements. In this paper, we relax this limitation by introducing the MultI-Level Embedding (MILE) framework -- a generic methodology allowing contemporary graph embedding methods to scale to large graphs. MILE repeatedly coarsens the graph into smaller ones using a hybrid matching technique to maintain the backbone structure of the graph. It then applies existing embedding methods on the coarse"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.09612","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/1802.09612/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":"2026-07-05T01:27:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KeZAbxtwzxDTev02+Y1i4i4tWnyo5I7baR2T1VfNBg8XeMiv/TMbmo3Qs3n+vR5uYuefU8SE1E+P3EypSWE7CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T04:11:42.357102Z"},"content_sha256":"396397b926e1475b52be8636d68a070c1bc4d6af3c82b5c57baa93770a086e00","schema_version":"1.0","event_id":"sha256:396397b926e1475b52be8636d68a070c1bc4d6af3c82b5c57baa93770a086e00"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB/bundle.json","state_url":"https://pith.science/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB/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":"2026-08-17T04:11:42Z","links":{"resolver":"https://pith.science/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB","bundle":"https://pith.science/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB/bundle.json","state":"https://pith.science/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CM5AKZUWNIQ2XJTTXSRBPTLRMB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CM5AKZUWNIQ2XJTTXSRBPTLRMB","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":"b5de55a384b1d293d22085c03b06733cab8d237efdbdb99852fe027ee2cf16dc","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-26T21:18:43Z","title_canon_sha256":"b5c046bbd6ab1bbbba5e5032adf08954c568e5f86be25f9bad3cba9f76df4845"},"schema_version":"1.0","source":{"id":"1802.09612","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.09612","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"arxiv_version","alias_value":"1802.09612v2","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.09612","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"pith_short_12","alias_value":"CM5AKZUWNIQ2","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"pith_short_16","alias_value":"CM5AKZUWNIQ2XJTT","created_at":"2026-07-05T01:27:00Z"},{"alias_kind":"pith_short_8","alias_value":"CM5AKZUW","created_at":"2026-07-05T01:27:00Z"}],"graph_snapshots":[{"event_id":"sha256:396397b926e1475b52be8636d68a070c1bc4d6af3c82b5c57baa93770a086e00","target":"graph","created_at":"2026-07-05T01:27:00Z","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/1802.09612/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently there has been a surge of interest in designing graph embedding methods. Few, if any, can scale to a large-sized graph with millions of nodes due to both computational complexity and memory requirements. In this paper, we relax this limitation by introducing the MultI-Level Embedding (MILE) framework -- a generic methodology allowing contemporary graph embedding methods to scale to large graphs. MILE repeatedly coarsens the graph into smaller ones using a hybrid matching technique to maintain the backbone structure of the graph. It then applies existing embedding methods on the coarse","authors_text":"Jiongqian Liang, Saket Gurukar, Srinivasan Parthasarathy","cross_cats":["cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-26T21:18:43Z","title":"MILE: A Multi-Level Framework for Scalable Graph Embedding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.09612","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:ba60333033b53ca836789134824afb50f46315b126f435abde6c63e00f576ab8","target":"record","created_at":"2026-07-05T01:27:00Z","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":"b5de55a384b1d293d22085c03b06733cab8d237efdbdb99852fe027ee2cf16dc","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-26T21:18:43Z","title_canon_sha256":"b5c046bbd6ab1bbbba5e5032adf08954c568e5f86be25f9bad3cba9f76df4845"},"schema_version":"1.0","source":{"id":"1802.09612","kind":"arxiv","version":2}},"canonical_sha256":"133a0566966a21aba673bca217cd716070b21b49ee895f306d8659bea136be78","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"133a0566966a21aba673bca217cd716070b21b49ee895f306d8659bea136be78","first_computed_at":"2026-07-05T01:27:00.205134Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:00.205134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MJwz5XvyzNcRUeXelduETllh4szPvxWC+kLMPgCbYAFqE1npsMHEavdscx+pVzcUEGGVOFhi2ptBrL7US+FABw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:00.205621Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.09612","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba60333033b53ca836789134824afb50f46315b126f435abde6c63e00f576ab8","sha256:396397b926e1475b52be8636d68a070c1bc4d6af3c82b5c57baa93770a086e00"],"state_sha256":"8248ced9e261972c4b45611efbccc5151e76716d2f5c19d89a8271ce86e5b7f6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xyi0is7jkWFl/QbAr/TRCFH+KxJSWam4tMTURnAKQcPpHtw1Fdhx6nKWEVGgUm6rUaJnIjzBU0B4slWd4OwEAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T04:11:42.369209Z","bundle_sha256":"55de9d796b70a63574156254f0a37084b253fe4bc821c3d4bdfba44e6095204f"}}