{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZVHNR27GY73T37JRE7JTFK2QPA","short_pith_number":"pith:ZVHNR27G","canonical_record":{"source":{"id":"2507.22434","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-30T07:26:40Z","cross_cats_sorted":[],"title_canon_sha256":"023fd252f1e191d9431b7fec6109b9a62d96a79c0614193dd3b431c80e8b7e92","abstract_canon_sha256":"d464a450dcbaab7410762f53549198d32c06b2997da9dbf18c546971d281b992"},"schema_version":"1.0"},"canonical_sha256":"cd4ed8ebe6c7f73dfd3127d332ab50783fd549162d70323fdd2693099e74dff3","source":{"kind":"arxiv","id":"2507.22434","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.22434","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"arxiv_version","alias_value":"2507.22434v2","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.22434","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"pith_short_12","alias_value":"ZVHNR27GY73T","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"pith_short_16","alias_value":"ZVHNR27GY73T37JR","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"pith_short_8","alias_value":"ZVHNR27G","created_at":"2026-07-05T11:50:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZVHNR27GY73T37JRE7JTFK2QPA","target":"record","payload":{"canonical_record":{"source":{"id":"2507.22434","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-30T07:26:40Z","cross_cats_sorted":[],"title_canon_sha256":"023fd252f1e191d9431b7fec6109b9a62d96a79c0614193dd3b431c80e8b7e92","abstract_canon_sha256":"d464a450dcbaab7410762f53549198d32c06b2997da9dbf18c546971d281b992"},"schema_version":"1.0"},"canonical_sha256":"cd4ed8ebe6c7f73dfd3127d332ab50783fd549162d70323fdd2693099e74dff3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:39.045101Z","signature_b64":"2KZitZWF1HhN79BIzgk8o/3NBezKfPawYcDuHuIcofvMFzLj4XTRx6q/npgzodP3Mw5scKqAS85Yi05sRGf4DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd4ed8ebe6c7f73dfd3127d332ab50783fd549162d70323fdd2693099e74dff3","last_reissued_at":"2026-07-05T11:50:39.044665Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:39.044665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.22434","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":"2026-07-05T11:50:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ic8Pon6n86/5Lo04CPAyg63kdHBWl/B3wFqDJnIqv5u43RNW24+qUmObFeZ3tP3/N7emq4btGvg9/gAChPMADg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T06:12:36.041364Z"},"content_sha256":"e814c9752f27bb33ff86ccd924b349c46ffb61e8d7a765b15352752283f0640c","schema_version":"1.0","event_id":"sha256:e814c9752f27bb33ff86ccd924b349c46ffb61e8d7a765b15352752283f0640c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZVHNR27GY73T37JRE7JTFK2QPA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RANA: Robust Active Learning for Noisy Network Alignment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Can Zhao, Xixun Lin, Yanan Cao, Yanmin Shang, Yixuan Nan, Zhuofan Li","submitted_at":"2025-07-30T07:26:40Z","abstract_excerpt":"Network alignment has attracted widespread attention in various fields. However, most existing works mainly focus on the problem of label sparsity, while overlooking the issue of noise in network alignment, which can substantially undermine model performance. Such noise mainly includes structural noise from noisy edges and labeling noise caused by human-induced and process-driven errors. To address these problems, we propose RANA, a Robust Active learning framework for noisy Network Alignment. RANA effectively tackles both structure noise and label noise while addressing the sparsity of anchor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.22434","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/2507.22434/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":"2026-07-05T11:50:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jwcyboYpe87QO8+Tc5hbjRPcNXuXhiVI/mkjRdZ50oXkyIYNlnWPPwp01J8pQ6Ddh4GiYaqkCyNK2XPCHB6WCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T06:12:36.042242Z"},"content_sha256":"d030cb923037cb1b3a04f86b2ec342f7bf3ccd943675eb61f27fb7eb474c181f","schema_version":"1.0","event_id":"sha256:d030cb923037cb1b3a04f86b2ec342f7bf3ccd943675eb61f27fb7eb474c181f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZVHNR27GY73T37JRE7JTFK2QPA/bundle.json","state_url":"https://pith.science/pith/ZVHNR27GY73T37JRE7JTFK2QPA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZVHNR27GY73T37JRE7JTFK2QPA/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":"2026-08-18T06:12:36Z","links":{"resolver":"https://pith.science/pith/ZVHNR27GY73T37JRE7JTFK2QPA","bundle":"https://pith.science/pith/ZVHNR27GY73T37JRE7JTFK2QPA/bundle.json","state":"https://pith.science/pith/ZVHNR27GY73T37JRE7JTFK2QPA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZVHNR27GY73T37JRE7JTFK2QPA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZVHNR27GY73T37JRE7JTFK2QPA","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":"d464a450dcbaab7410762f53549198d32c06b2997da9dbf18c546971d281b992","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-30T07:26:40Z","title_canon_sha256":"023fd252f1e191d9431b7fec6109b9a62d96a79c0614193dd3b431c80e8b7e92"},"schema_version":"1.0","source":{"id":"2507.22434","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.22434","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"arxiv_version","alias_value":"2507.22434v2","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.22434","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"pith_short_12","alias_value":"ZVHNR27GY73T","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"pith_short_16","alias_value":"ZVHNR27GY73T37JR","created_at":"2026-07-05T11:50:39Z"},{"alias_kind":"pith_short_8","alias_value":"ZVHNR27G","created_at":"2026-07-05T11:50:39Z"}],"graph_snapshots":[{"event_id":"sha256:d030cb923037cb1b3a04f86b2ec342f7bf3ccd943675eb61f27fb7eb474c181f","target":"graph","created_at":"2026-07-05T11:50:39Z","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/2507.22434/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Network alignment has attracted widespread attention in various fields. However, most existing works mainly focus on the problem of label sparsity, while overlooking the issue of noise in network alignment, which can substantially undermine model performance. Such noise mainly includes structural noise from noisy edges and labeling noise caused by human-induced and process-driven errors. To address these problems, we propose RANA, a Robust Active learning framework for noisy Network Alignment. RANA effectively tackles both structure noise and label noise while addressing the sparsity of anchor","authors_text":"Can Zhao, Xixun Lin, Yanan Cao, Yanmin Shang, Yixuan Nan, Zhuofan Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-30T07:26:40Z","title":"RANA: Robust Active Learning for Noisy Network Alignment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.22434","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:e814c9752f27bb33ff86ccd924b349c46ffb61e8d7a765b15352752283f0640c","target":"record","created_at":"2026-07-05T11:50:39Z","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":"d464a450dcbaab7410762f53549198d32c06b2997da9dbf18c546971d281b992","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-30T07:26:40Z","title_canon_sha256":"023fd252f1e191d9431b7fec6109b9a62d96a79c0614193dd3b431c80e8b7e92"},"schema_version":"1.0","source":{"id":"2507.22434","kind":"arxiv","version":2}},"canonical_sha256":"cd4ed8ebe6c7f73dfd3127d332ab50783fd549162d70323fdd2693099e74dff3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd4ed8ebe6c7f73dfd3127d332ab50783fd549162d70323fdd2693099e74dff3","first_computed_at":"2026-07-05T11:50:39.044665Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:39.044665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2KZitZWF1HhN79BIzgk8o/3NBezKfPawYcDuHuIcofvMFzLj4XTRx6q/npgzodP3Mw5scKqAS85Yi05sRGf4DA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:39.045101Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.22434","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e814c9752f27bb33ff86ccd924b349c46ffb61e8d7a765b15352752283f0640c","sha256:d030cb923037cb1b3a04f86b2ec342f7bf3ccd943675eb61f27fb7eb474c181f"],"state_sha256":"9b31de276025056de1131e98be444f56acd066df0f1f4fca792266270e6a1253"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RqTaWG5ruuZw8XWTcnCa+RVGrKB/MGzEiiKMb6s9D9rlBahylh/vRtn1kbwTi9DHQlIcwN778tMZ0VyvFJY3Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T06:12:36.047879Z","bundle_sha256":"f28499f2420f7d64aa833dbd6dc07f4f6ee89c6bf268a95a28a11565de64a61b"}}