{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:ODZJCCYNCTWYMAKFCYXSUJMWJY","short_pith_number":"pith:ODZJCCYN","schema_version":"1.0","canonical_sha256":"70f2910b0d14ed860145162f2a25964e322b6a94b5d9ad73b7fbc0a6f86ac932","source":{"kind":"arxiv","id":"1812.07439","version":1},"attestation_state":"computed","paper":{"title":"Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Daniel Lund\\'en, David Broman, Fredrik Ronquist, Lawrence M. Murray","submitted_at":"2018-12-18T15:42:55Z","abstract_excerpt":"Probabilistic programming is a programming paradigm for expressing flexible probabilistic models. Implementations of probabilistic programming languages employ a variety of inference algorithms, where sequential Monte Carlo methods are commonly used. A problem with current state-of-the-art implementations using sequential Monte Carlo inference is the alignment of program synchronization points. We propose a new static analysis approach based on the 0-CFA algorithm for automatically aligning higher-order probabilistic programs. We evaluate the automatic alignment on a phylogenetic model, showin"},"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":"1812.07439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PL","submitted_at":"2018-12-18T15:42:55Z","cross_cats_sorted":[],"title_canon_sha256":"43a5b97f37590cec713dbc51a5851ba5474493fc0c763cec0a8a5c7f3135f517","abstract_canon_sha256":"3c6cbf42c228cd37ae5c5ed8cc402931cd91915a5df5f30dceebb77e8cc450bb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:00.511540Z","signature_b64":"H/vw8lHM6+bGMKS83QT2yTtL4Mo4saJ+wENJ24QtEHxjC88zTjQxk6zapp+YFsVkFgkNBdoR7yePKXYxAc7RDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70f2910b0d14ed860145162f2a25964e322b6a94b5d9ad73b7fbc0a6f86ac932","last_reissued_at":"2026-05-17T23:58:00.510791Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:00.510791Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automatic Alignment of Sequential Monte Carlo Inference in Higher-Order Probabilistic Programs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Daniel Lund\\'en, David Broman, Fredrik Ronquist, Lawrence M. Murray","submitted_at":"2018-12-18T15:42:55Z","abstract_excerpt":"Probabilistic programming is a programming paradigm for expressing flexible probabilistic models. Implementations of probabilistic programming languages employ a variety of inference algorithms, where sequential Monte Carlo methods are commonly used. A problem with current state-of-the-art implementations using sequential Monte Carlo inference is the alignment of program synchronization points. We propose a new static analysis approach based on the 0-CFA algorithm for automatically aligning higher-order probabilistic programs. We evaluate the automatic alignment on a phylogenetic model, showin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.07439","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":"1812.07439","created_at":"2026-05-17T23:58:00.510916+00:00"},{"alias_kind":"arxiv_version","alias_value":"1812.07439v1","created_at":"2026-05-17T23:58:00.510916+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.07439","created_at":"2026-05-17T23:58:00.510916+00:00"},{"alias_kind":"pith_short_12","alias_value":"ODZJCCYNCTWY","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_16","alias_value":"ODZJCCYNCTWYMAKF","created_at":"2026-05-18T12:32:43.782077+00:00"},{"alias_kind":"pith_short_8","alias_value":"ODZJCCYN","created_at":"2026-05-18T12:32:43.782077+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/ODZJCCYNCTWYMAKFCYXSUJMWJY","json":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY.json","graph_json":"https://pith.science/api/pith-number/ODZJCCYNCTWYMAKFCYXSUJMWJY/graph.json","events_json":"https://pith.science/api/pith-number/ODZJCCYNCTWYMAKFCYXSUJMWJY/events.json","paper":"https://pith.science/paper/ODZJCCYN"},"agent_actions":{"view_html":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY","download_json":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY.json","view_paper":"https://pith.science/paper/ODZJCCYN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1812.07439&json=true","fetch_graph":"https://pith.science/api/pith-number/ODZJCCYNCTWYMAKFCYXSUJMWJY/graph.json","fetch_events":"https://pith.science/api/pith-number/ODZJCCYNCTWYMAKFCYXSUJMWJY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY/action/storage_attestation","attest_author":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY/action/author_attestation","sign_citation":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY/action/citation_signature","submit_replication":"https://pith.science/pith/ODZJCCYNCTWYMAKFCYXSUJMWJY/action/replication_record"}},"created_at":"2026-05-17T23:58:00.510916+00:00","updated_at":"2026-05-17T23:58:00.510916+00:00"}