{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:GMPK46BJOLPCJ2ZTSWM525G7RH","short_pith_number":"pith:GMPK46BJ","schema_version":"1.0","canonical_sha256":"331eae782972de24eb339599dd74df89fa7d2c38f732116aefd3fcc0ec0760c7","source":{"kind":"arxiv","id":"2608.05205","version":1},"attestation_state":"computed","paper":{"title":"Abstract Event Causal Rules: Induction and Application","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bang Wang, Peiqiong Chen, Ziwei Zheng","submitted_at":"2026-08-05T07:44:22Z","abstract_excerpt":"Event-centric intelligent analytical systems heavily depend on explicit causal event knowledge for risk early warning, decision-making support and narrative comprehension. Nevertheless, existing instance-level causal pairs suffer severe generalization deficits on low-frequency long-tail and unseen event combinations. To address this limitation, this work proposes Abstract Event Causal Rule (AECR), a novel relation-level causal abstraction paradigm that transforms concrete cause-effect pairs into generalized abstract causal logic while retaining their intrinsic causal relationships. We design a"},"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":"2608.05205","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-05T07:44:22Z","cross_cats_sorted":[],"title_canon_sha256":"b28c03edfcf1953dad543046c559c7e76cb2d476f916115bc2fc674691940ca6","abstract_canon_sha256":"f1099c2dfb1f7cff83e7191c6b14f799fe901501ac3945fedfad9f439004c541"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T00:46:31.529912Z","signature_b64":"8hA+s4e7MPMaOvtGJ2Y+6pKnYvbHptYBQayUgSQrM8rkevrzg8P5c3pv0fHa7hBP1MnZS896VRIxPiwC1XBEBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"331eae782972de24eb339599dd74df89fa7d2c38f732116aefd3fcc0ec0760c7","last_reissued_at":"2026-08-07T00:46:31.528421Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T00:46:31.528421Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Abstract Event Causal Rules: Induction and Application","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bang Wang, Peiqiong Chen, Ziwei Zheng","submitted_at":"2026-08-05T07:44:22Z","abstract_excerpt":"Event-centric intelligent analytical systems heavily depend on explicit causal event knowledge for risk early warning, decision-making support and narrative comprehension. Nevertheless, existing instance-level causal pairs suffer severe generalization deficits on low-frequency long-tail and unseen event combinations. To address this limitation, this work proposes Abstract Event Causal Rule (AECR), a novel relation-level causal abstraction paradigm that transforms concrete cause-effect pairs into generalized abstract causal logic while retaining their intrinsic causal relationships. We design a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05205","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/2608.05205/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":"2608.05205","created_at":"2026-08-07T00:46:31.529802+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.05205v1","created_at":"2026-08-07T00:46:31.529802+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05205","created_at":"2026-08-07T00:46:31.529802+00:00"},{"alias_kind":"pith_short_12","alias_value":"GMPK46BJOLPC","created_at":"2026-08-07T00:46:31.529802+00:00"},{"alias_kind":"pith_short_16","alias_value":"GMPK46BJOLPCJ2ZT","created_at":"2026-08-07T00:46:31.529802+00:00"},{"alias_kind":"pith_short_8","alias_value":"GMPK46BJ","created_at":"2026-08-07T00:46:31.529802+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/GMPK46BJOLPCJ2ZTSWM525G7RH","json":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH.json","graph_json":"https://pith.science/api/pith-number/GMPK46BJOLPCJ2ZTSWM525G7RH/graph.json","events_json":"https://pith.science/api/pith-number/GMPK46BJOLPCJ2ZTSWM525G7RH/events.json","paper":"https://pith.science/paper/GMPK46BJ"},"agent_actions":{"view_html":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH","download_json":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH.json","view_paper":"https://pith.science/paper/GMPK46BJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.05205&json=true","fetch_graph":"https://pith.science/api/pith-number/GMPK46BJOLPCJ2ZTSWM525G7RH/graph.json","fetch_events":"https://pith.science/api/pith-number/GMPK46BJOLPCJ2ZTSWM525G7RH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH/action/storage_attestation","attest_author":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH/action/author_attestation","sign_citation":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH/action/citation_signature","submit_replication":"https://pith.science/pith/GMPK46BJOLPCJ2ZTSWM525G7RH/action/replication_record"}},"created_at":"2026-08-07T00:46:31.529802+00:00","updated_at":"2026-08-07T00:46:31.529802+00:00"}