{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:JAVSRWGRQAGMJEN7B2I5CIRQOB","short_pith_number":"pith:JAVSRWGR","schema_version":"1.0","canonical_sha256":"482b28d8d1800cc491bf0e91d122307052ffa408db6846f91703110ca4cc56b5","source":{"kind":"arxiv","id":"2508.20922","version":1},"attestation_state":"computed","paper":{"title":"Static Factorisation of Probabilistic Programs With User-Labelled Sample Statements and While Loops","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"J\\\"urgen Cito, Markus B\\\"ock","submitted_at":"2025-08-28T15:51:16Z","abstract_excerpt":"It is commonly known that any Bayesian network can be implemented as a probabilistic program, but the reverse direction is not so clear. In this work, we address the open question to what extent a probabilistic program with user-labelled sample statements and while loops - features found in languages like Gen, Turing, and Pyro - can be represented graphically. To this end, we extend existing operational semantics to support these language features. By translating a program to its control-flow graph, we define a sound static analysis that approximates the dependency structure of the random vari"},"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":"2508.20922","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.PL","submitted_at":"2025-08-28T15:51:16Z","cross_cats_sorted":[],"title_canon_sha256":"cb1e530634819548d9daa25a82bd4a2a04612d40b2d971aec4866a48c1217efc","abstract_canon_sha256":"f9cb07f0e647b60f5f4d3644307da44d6ae8439f6b776092f8c2e42efb833fe9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:01:13.527950Z","signature_b64":"BGiQAdsNNGv47mfFGkzLsvka1wakLtzV6mCq6dp8TjYQWjgMmSJPjcppBv2QKMQY/HI/atGxIBYL7ps4Tl6ZBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"482b28d8d1800cc491bf0e91d122307052ffa408db6846f91703110ca4cc56b5","last_reissued_at":"2026-07-05T12:01:13.527457Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:01:13.527457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Static Factorisation of Probabilistic Programs With User-Labelled Sample Statements and While Loops","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"J\\\"urgen Cito, Markus B\\\"ock","submitted_at":"2025-08-28T15:51:16Z","abstract_excerpt":"It is commonly known that any Bayesian network can be implemented as a probabilistic program, but the reverse direction is not so clear. In this work, we address the open question to what extent a probabilistic program with user-labelled sample statements and while loops - features found in languages like Gen, Turing, and Pyro - can be represented graphically. To this end, we extend existing operational semantics to support these language features. By translating a program to its control-flow graph, we define a sound static analysis that approximates the dependency structure of the random vari"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.20922","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/2508.20922/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":"2508.20922","created_at":"2026-07-05T12:01:13.527515+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.20922v1","created_at":"2026-07-05T12:01:13.527515+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.20922","created_at":"2026-07-05T12:01:13.527515+00:00"},{"alias_kind":"pith_short_12","alias_value":"JAVSRWGRQAGM","created_at":"2026-07-05T12:01:13.527515+00:00"},{"alias_kind":"pith_short_16","alias_value":"JAVSRWGRQAGMJEN7","created_at":"2026-07-05T12:01:13.527515+00:00"},{"alias_kind":"pith_short_8","alias_value":"JAVSRWGR","created_at":"2026-07-05T12:01:13.527515+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2606.05348","citing_title":"Incremental Computation for Efficient Programmable Inference in Probabilistic Programs","ref_index":7,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB","json":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB.json","graph_json":"https://pith.science/api/pith-number/JAVSRWGRQAGMJEN7B2I5CIRQOB/graph.json","events_json":"https://pith.science/api/pith-number/JAVSRWGRQAGMJEN7B2I5CIRQOB/events.json","paper":"https://pith.science/paper/JAVSRWGR"},"agent_actions":{"view_html":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB","download_json":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB.json","view_paper":"https://pith.science/paper/JAVSRWGR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.20922&json=true","fetch_graph":"https://pith.science/api/pith-number/JAVSRWGRQAGMJEN7B2I5CIRQOB/graph.json","fetch_events":"https://pith.science/api/pith-number/JAVSRWGRQAGMJEN7B2I5CIRQOB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB/action/storage_attestation","attest_author":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB/action/author_attestation","sign_citation":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB/action/citation_signature","submit_replication":"https://pith.science/pith/JAVSRWGRQAGMJEN7B2I5CIRQOB/action/replication_record"}},"created_at":"2026-07-05T12:01:13.527515+00:00","updated_at":"2026-07-05T12:01:13.527515+00:00"}