{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:7JOBM43ZS2SMSFFM2TB64NOR5G","short_pith_number":"pith:7JOBM43Z","schema_version":"1.0","canonical_sha256":"fa5c16737996a4c914acd4c3ee35d1e9bbc44260f7f84f93c180c5758172881d","source":{"kind":"arxiv","id":"2305.10227","version":1},"attestation_state":"computed","paper":{"title":"Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI","stat.ML"],"primary_cat":"cs.LG","authors_text":"David Steurer, Jingqiu Ding, Tommaso d'Orsi, Yiding Hua","submitted_at":"2023-05-17T14:03:47Z","abstract_excerpt":"We study robust community detection in the context of node-corrupted stochastic block model, where an adversary can arbitrarily modify all the edges incident to a fraction of the $n$ vertices. We present the first polynomial-time algorithm that achieves weak recovery at the Kesten-Stigum threshold even in the presence of a small constant fraction of corrupted nodes. Prior to this work, even state-of-the-art robust algorithms were known to break under such node corruption adversaries, when close to the Kesten-Stigum threshold.\n  We further extend our techniques to the $Z_2$ synchronization prob"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2305.10227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-17T14:03:47Z","cross_cats_sorted":["cs.SI","stat.ML"],"title_canon_sha256":"7bacddb476f97f11f4f8aea8a37ffc59afa35b2b137372285b1ee974d810d250","abstract_canon_sha256":"9f5c679646cdaf01220b45494e08775407916590a606a55c6e9a8e6604991f9e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:45:17.382881Z","signature_b64":"CmsAvT/Rf/QNE3PjocaJkcpxmgGswHe5ZMU6U1fxOQp5N3pTkD8nIhNjx5mkVe/gE5yPEuUPhLG5TX26Uo6nCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa5c16737996a4c914acd4c3ee35d1e9bbc44260f7f84f93c180c5758172881d","last_reissued_at":"2026-07-05T06:45:17.382310Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:45:17.382310Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI","stat.ML"],"primary_cat":"cs.LG","authors_text":"David Steurer, Jingqiu Ding, Tommaso d'Orsi, Yiding Hua","submitted_at":"2023-05-17T14:03:47Z","abstract_excerpt":"We study robust community detection in the context of node-corrupted stochastic block model, where an adversary can arbitrarily modify all the edges incident to a fraction of the $n$ vertices. We present the first polynomial-time algorithm that achieves weak recovery at the Kesten-Stigum threshold even in the presence of a small constant fraction of corrupted nodes. Prior to this work, even state-of-the-art robust algorithms were known to break under such node corruption adversaries, when close to the Kesten-Stigum threshold.\n  We further extend our techniques to the $Z_2$ synchronization prob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.10227","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/2305.10227/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2305.10227","created_at":"2026-07-05T06:45:17.382377+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.10227v1","created_at":"2026-07-05T06:45:17.382377+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.10227","created_at":"2026-07-05T06:45:17.382377+00:00"},{"alias_kind":"pith_short_12","alias_value":"7JOBM43ZS2SM","created_at":"2026-07-05T06:45:17.382377+00:00"},{"alias_kind":"pith_short_16","alias_value":"7JOBM43ZS2SMSFFM","created_at":"2026-07-05T06:45:17.382377+00:00"},{"alias_kind":"pith_short_8","alias_value":"7JOBM43Z","created_at":"2026-07-05T06:45:17.382377+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.03657","citing_title":"SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph Search","ref_index":8,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G","json":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G.json","graph_json":"https://pith.science/api/pith-number/7JOBM43ZS2SMSFFM2TB64NOR5G/graph.json","events_json":"https://pith.science/api/pith-number/7JOBM43ZS2SMSFFM2TB64NOR5G/events.json","paper":"https://pith.science/paper/7JOBM43Z"},"agent_actions":{"view_html":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G","download_json":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G.json","view_paper":"https://pith.science/paper/7JOBM43Z","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.10227&json=true","fetch_graph":"https://pith.science/api/pith-number/7JOBM43ZS2SMSFFM2TB64NOR5G/graph.json","fetch_events":"https://pith.science/api/pith-number/7JOBM43ZS2SMSFFM2TB64NOR5G/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G/action/storage_attestation","attest_author":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G/action/author_attestation","sign_citation":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G/action/citation_signature","submit_replication":"https://pith.science/pith/7JOBM43ZS2SMSFFM2TB64NOR5G/action/replication_record"}},"created_at":"2026-07-05T06:45:17.382377+00:00","updated_at":"2026-07-05T06:45:17.382377+00:00"}