{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:LVGGXTOOTMQC4DWPXB5KCKLOMN","short_pith_number":"pith:LVGGXTOO","schema_version":"1.0","canonical_sha256":"5d4c6bcdce9b202e0ecfb87aa1296e6378d6c6e7a83ddd13c3ece192cd2c1a42","source":{"kind":"arxiv","id":"1306.0751","version":1},"attestation_state":"computed","paper":{"title":"First-Order Decomposition Trees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Hendrik Blockeel, Jesse Davis, Nima Taghipour","submitted_at":"2013-06-04T12:43:07Z","abstract_excerpt":"Lifting attempts to speed up probabilistic inference by exploiting symmetries in the model. Exact lifted inference methods, like their propositional counterparts, work by recursively decomposing the model and the problem. In the propositional case, there exist formal structures, such as decomposition trees (dtrees), that represent such a decomposition and allow us to determine the complexity of inference a priori. However, there is currently no equivalent structure nor analogous complexity results for lifted inference. In this paper, we introduce FO-dtrees, which upgrade propositional dtrees t"},"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":"1306.0751","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2013-06-04T12:43:07Z","cross_cats_sorted":[],"title_canon_sha256":"f6334c0c36dfea18f161b6a128d7806450e5e289aaa3a58d362285220f8b5946","abstract_canon_sha256":"658bd33dd2e0eec1418ea09bb245dacb8854594bbb601e0a44551a26797c73ab"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:21:53.293209Z","signature_b64":"L5yB/dZU3Ucj1wWRQrGPXMY7tTmmFF3sH2B/BzE5xYfjfEVvGCvJySBcBHKw9dP0fBRycvXYhtlIwD3wCiL9Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d4c6bcdce9b202e0ecfb87aa1296e6378d6c6e7a83ddd13c3ece192cd2c1a42","last_reissued_at":"2026-05-18T03:21:53.292832Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:21:53.292832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"First-Order Decomposition Trees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Hendrik Blockeel, Jesse Davis, Nima Taghipour","submitted_at":"2013-06-04T12:43:07Z","abstract_excerpt":"Lifting attempts to speed up probabilistic inference by exploiting symmetries in the model. Exact lifted inference methods, like their propositional counterparts, work by recursively decomposing the model and the problem. In the propositional case, there exist formal structures, such as decomposition trees (dtrees), that represent such a decomposition and allow us to determine the complexity of inference a priori. However, there is currently no equivalent structure nor analogous complexity results for lifted inference. In this paper, we introduce FO-dtrees, which upgrade propositional dtrees t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1306.0751","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":""},"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":"1306.0751","created_at":"2026-05-18T03:21:53.292889+00:00"},{"alias_kind":"arxiv_version","alias_value":"1306.0751v1","created_at":"2026-05-18T03:21:53.292889+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1306.0751","created_at":"2026-05-18T03:21:53.292889+00:00"},{"alias_kind":"pith_short_12","alias_value":"LVGGXTOOTMQC","created_at":"2026-05-18T12:27:51.066281+00:00"},{"alias_kind":"pith_short_16","alias_value":"LVGGXTOOTMQC4DWP","created_at":"2026-05-18T12:27:51.066281+00:00"},{"alias_kind":"pith_short_8","alias_value":"LVGGXTOO","created_at":"2026-05-18T12:27:51.066281+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/LVGGXTOOTMQC4DWPXB5KCKLOMN","json":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN.json","graph_json":"https://pith.science/api/pith-number/LVGGXTOOTMQC4DWPXB5KCKLOMN/graph.json","events_json":"https://pith.science/api/pith-number/LVGGXTOOTMQC4DWPXB5KCKLOMN/events.json","paper":"https://pith.science/paper/LVGGXTOO"},"agent_actions":{"view_html":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN","download_json":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN.json","view_paper":"https://pith.science/paper/LVGGXTOO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1306.0751&json=true","fetch_graph":"https://pith.science/api/pith-number/LVGGXTOOTMQC4DWPXB5KCKLOMN/graph.json","fetch_events":"https://pith.science/api/pith-number/LVGGXTOOTMQC4DWPXB5KCKLOMN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN/action/storage_attestation","attest_author":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN/action/author_attestation","sign_citation":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN/action/citation_signature","submit_replication":"https://pith.science/pith/LVGGXTOOTMQC4DWPXB5KCKLOMN/action/replication_record"}},"created_at":"2026-05-18T03:21:53.292889+00:00","updated_at":"2026-05-18T03:21:53.292889+00:00"}