{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:2U3YWYXXE24O3YXQR7LR5AXOOE","short_pith_number":"pith:2U3YWYXX","schema_version":"1.0","canonical_sha256":"d5378b62f726b8ede2f08fd71e82ee713adbb72e00adbdac8b2b212971a978b5","source":{"kind":"arxiv","id":"2502.05472","version":1},"attestation_state":"computed","paper":{"title":"Robust Deep Signed Graph Clustering via Weak Balance Theory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Lejian Liao, Mingzhong Wang, Peiyao Zhao, Xin Li, Xueying Zhu, Zeyu Zhang","submitted_at":"2025-02-08T07:14:17Z","abstract_excerpt":"Signed graph clustering is a critical technique for discovering community structures in graphs that exhibit both positive and negative relationships. We have identified two significant challenges in this domain: i) existing signed spectral methods are highly vulnerable to noise, which is prevalent in real-world scenarios; ii) the guiding principle ``an enemy of my enemy is my friend'', rooted in \\textit{Social Balance Theory}, often narrows or disrupts cluster boundaries in mainstream signed graph neural networks. Addressing these challenges, we propose the \\underline{D}eep \\underline{S}igned "},"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":"2502.05472","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2025-02-08T07:14:17Z","cross_cats_sorted":[],"title_canon_sha256":"916cec5ee72be6c6ad2cf908b3dc78a9f97f337fa175fd64531453d434f8d91b","abstract_canon_sha256":"5908d7a702220548bfeaf51a91dd9bca767c4620562bccfabc7521f164c63fef"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:11:38.586878Z","signature_b64":"zqAI70H28blSYecH35LZVVcXnoJa6fWCLg3iVKlslTd/cE8N/kb7bBLBk5Gp+jEx1QCGniIzYkqXxFW/Zz2AAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5378b62f726b8ede2f08fd71e82ee713adbb72e00adbdac8b2b212971a978b5","last_reissued_at":"2026-07-05T10:11:38.586472Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:11:38.586472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Robust Deep Signed Graph Clustering via Weak Balance Theory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Lejian Liao, Mingzhong Wang, Peiyao Zhao, Xin Li, Xueying Zhu, Zeyu Zhang","submitted_at":"2025-02-08T07:14:17Z","abstract_excerpt":"Signed graph clustering is a critical technique for discovering community structures in graphs that exhibit both positive and negative relationships. We have identified two significant challenges in this domain: i) existing signed spectral methods are highly vulnerable to noise, which is prevalent in real-world scenarios; ii) the guiding principle ``an enemy of my enemy is my friend'', rooted in \\textit{Social Balance Theory}, often narrows or disrupts cluster boundaries in mainstream signed graph neural networks. Addressing these challenges, we propose the \\underline{D}eep \\underline{S}igned "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05472","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/2502.05472/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":"2502.05472","created_at":"2026-07-05T10:11:38.586526+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.05472v1","created_at":"2026-07-05T10:11:38.586526+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05472","created_at":"2026-07-05T10:11:38.586526+00:00"},{"alias_kind":"pith_short_12","alias_value":"2U3YWYXXE24O","created_at":"2026-07-05T10:11:38.586526+00:00"},{"alias_kind":"pith_short_16","alias_value":"2U3YWYXXE24O3YXQ","created_at":"2026-07-05T10:11:38.586526+00:00"},{"alias_kind":"pith_short_8","alias_value":"2U3YWYXX","created_at":"2026-07-05T10:11:38.586526+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE","json":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE.json","graph_json":"https://pith.science/api/pith-number/2U3YWYXXE24O3YXQR7LR5AXOOE/graph.json","events_json":"https://pith.science/api/pith-number/2U3YWYXXE24O3YXQR7LR5AXOOE/events.json","paper":"https://pith.science/paper/2U3YWYXX"},"agent_actions":{"view_html":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE","download_json":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE.json","view_paper":"https://pith.science/paper/2U3YWYXX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.05472&json=true","fetch_graph":"https://pith.science/api/pith-number/2U3YWYXXE24O3YXQR7LR5AXOOE/graph.json","fetch_events":"https://pith.science/api/pith-number/2U3YWYXXE24O3YXQR7LR5AXOOE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE/action/storage_attestation","attest_author":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE/action/author_attestation","sign_citation":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE/action/citation_signature","submit_replication":"https://pith.science/pith/2U3YWYXXE24O3YXQR7LR5AXOOE/action/replication_record"}},"created_at":"2026-07-05T10:11:38.586526+00:00","updated_at":"2026-07-05T10:11:38.586526+00:00"}