{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:C3CM2ADBL7FJVTYYQW5RIL3OA6","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"04150c8d04a66783819ad12c2954530ebaeed072c9b9ad14619d50ac0ae41220","cross_cats_sorted":["q-bio.GN","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T06:10:54Z","title_canon_sha256":"b7b037c48aa78a729f152fefdf68b9687f8cfd31781cd98bb34096628f232fa4"},"schema_version":"1.0","source":{"id":"2401.15903","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.15903","created_at":"2026-07-05T07:38:41Z"},{"alias_kind":"arxiv_version","alias_value":"2401.15903v1","created_at":"2026-07-05T07:38:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.15903","created_at":"2026-07-05T07:38:41Z"},{"alias_kind":"pith_short_12","alias_value":"C3CM2ADBL7FJ","created_at":"2026-07-05T07:38:41Z"},{"alias_kind":"pith_short_16","alias_value":"C3CM2ADBL7FJVTYY","created_at":"2026-07-05T07:38:41Z"},{"alias_kind":"pith_short_8","alias_value":"C3CM2ADB","created_at":"2026-07-05T07:38:41Z"}],"graph_snapshots":[{"event_id":"sha256:4ff8ac4a4e9c5caeccaffc0417694990f4ceaf0951b162167a05dda44c4c382b","target":"graph","created_at":"2026-07-05T07:38:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2401.15903/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Generative Models (DGMs) are versatile tools for learning data representations while adequately incorporating domain knowledge such as the specification of conditional probability distributions. Recently proposed DGMs tackle the important task of comparing data sets from different sources. One such example is the setting of contrastive analysis that focuses on describing patterns that are enriched in a target data set compared to a background data set. The practical deployment of those models often assumes that DGMs naturally infer interpretable and modular latent representations, which i","authors_text":"Aviv Regev, Ehsan Hajiramezanali, Jan-Christian Huetter, Jonathan Pritchard, Romain Lopez","cross_cats":["q-bio.GN","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T06:10:54Z","title":"Toward the Identifiability of Comparative Deep Generative Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.15903","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:602c257bb9e6a6026c50449dd24e14de8a1dc48b5069390a7557137ee0384500","target":"record","created_at":"2026-07-05T07:38:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"04150c8d04a66783819ad12c2954530ebaeed072c9b9ad14619d50ac0ae41220","cross_cats_sorted":["q-bio.GN","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T06:10:54Z","title_canon_sha256":"b7b037c48aa78a729f152fefdf68b9687f8cfd31781cd98bb34096628f232fa4"},"schema_version":"1.0","source":{"id":"2401.15903","kind":"arxiv","version":1}},"canonical_sha256":"16c4cd00615fca9acf1885bb142f6e07b409706237e32019a81bbc148f93e708","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16c4cd00615fca9acf1885bb142f6e07b409706237e32019a81bbc148f93e708","first_computed_at":"2026-07-05T07:38:41.215497Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:38:41.215497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WjiTpIcHDoN6xzF2iSdnHQp/g10uWv06u2TvRNJ0Umr5TvKgpYV0aN88C9qD7ixSDWfbf7rufBc69cf5YzsuCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:38:41.216005Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.15903","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:602c257bb9e6a6026c50449dd24e14de8a1dc48b5069390a7557137ee0384500","sha256:4ff8ac4a4e9c5caeccaffc0417694990f4ceaf0951b162167a05dda44c4c382b"],"state_sha256":"4bf1b43ba6df50aa78a346c9dfcc11ea57c42bba134237877d6ea375664529b4"}