{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:DN3ARTYQAI6K2WDSSQ776GDOHR","short_pith_number":"pith:DN3ARTYQ","schema_version":"1.0","canonical_sha256":"1b7608cf10023cad5872943fff186e3c75c4fde7baad45ea8ef2d7b8af3e59a5","source":{"kind":"arxiv","id":"2605.18633","version":1},"attestation_state":"computed","paper":{"title":"Stable Causal Discovery via Directed Acyclic Graph Aggregation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.ME","authors_text":"Chenglong Ye, Chunlin Li, Yue Wang, Yunan Wu","submitted_at":"2026-05-18T16:41:31Z","abstract_excerpt":"Directed Acyclic Graphs (DAGs) are central to uncovering causal structure in complex systems, yet learning a single DAG from data is often challenging: model uncertainty, finite samples, and a combinatorially large search space frequently yield unstable estimates. We propose DAGgr, a model averaging framework that aggregates multiple candidate DAGs into a single stable representation. Candidate graphs are weighted by their out-of-sample predictive likelihood across repeated data splits, and a thresholding rule on the resulting edge-importance scores guarantees that the aggregated graph is itse"},"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":"2605.18633","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2026-05-18T16:41:31Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e3a6fd851ab9b79e28b1234c045c1fbabb5eb7d7b90691d4971a7438f6f5ae95","abstract_canon_sha256":"d9b6ec0ed51fbf996d3906cab004cf879e312db58a0e8a0d2396bcfb6dcd4e91"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:06:11.825311Z","signature_b64":"KF8BigZUbxi9Xb8iA3t9RXvZUIDrgGCueLNF7EtX6+/EjiEZadbTV+xXDyodlN55ofO28q1W6j0Q8x1ap9p3Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b7608cf10023cad5872943fff186e3c75c4fde7baad45ea8ef2d7b8af3e59a5","last_reissued_at":"2026-05-20T00:06:11.824508Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:06:11.824508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Stable Causal Discovery via Directed Acyclic Graph Aggregation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.ME","authors_text":"Chenglong Ye, Chunlin Li, Yue Wang, Yunan Wu","submitted_at":"2026-05-18T16:41:31Z","abstract_excerpt":"Directed Acyclic Graphs (DAGs) are central to uncovering causal structure in complex systems, yet learning a single DAG from data is often challenging: model uncertainty, finite samples, and a combinatorially large search space frequently yield unstable estimates. We propose DAGgr, a model averaging framework that aggregates multiple candidate DAGs into a single stable representation. Candidate graphs are weighted by their out-of-sample predictive likelihood across repeated data splits, and a thresholding rule on the resulting edge-importance scores guarantees that the aggregated graph is itse"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18633","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/2605.18633/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-20T00:01:59.200395Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"359f3a1049cf5ef9190c37396aa0ab2af3beebde01a30ba47add528ed90d50b9"},"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":"2605.18633","created_at":"2026-05-20T00:06:11.824630+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.18633v1","created_at":"2026-05-20T00:06:11.824630+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18633","created_at":"2026-05-20T00:06:11.824630+00:00"},{"alias_kind":"pith_short_12","alias_value":"DN3ARTYQAI6K","created_at":"2026-05-20T00:06:11.824630+00:00"},{"alias_kind":"pith_short_16","alias_value":"DN3ARTYQAI6K2WDS","created_at":"2026-05-20T00:06:11.824630+00:00"},{"alias_kind":"pith_short_8","alias_value":"DN3ARTYQ","created_at":"2026-05-20T00:06:11.824630+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/DN3ARTYQAI6K2WDSSQ776GDOHR","json":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR.json","graph_json":"https://pith.science/api/pith-number/DN3ARTYQAI6K2WDSSQ776GDOHR/graph.json","events_json":"https://pith.science/api/pith-number/DN3ARTYQAI6K2WDSSQ776GDOHR/events.json","paper":"https://pith.science/paper/DN3ARTYQ"},"agent_actions":{"view_html":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR","download_json":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR.json","view_paper":"https://pith.science/paper/DN3ARTYQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.18633&json=true","fetch_graph":"https://pith.science/api/pith-number/DN3ARTYQAI6K2WDSSQ776GDOHR/graph.json","fetch_events":"https://pith.science/api/pith-number/DN3ARTYQAI6K2WDSSQ776GDOHR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR/action/storage_attestation","attest_author":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR/action/author_attestation","sign_citation":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR/action/citation_signature","submit_replication":"https://pith.science/pith/DN3ARTYQAI6K2WDSSQ776GDOHR/action/replication_record"}},"created_at":"2026-05-20T00:06:11.824630+00:00","updated_at":"2026-05-20T00:06:11.824630+00:00"}