{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:LD7GPCRYGUYGNCTVJRUCTZDDB6","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":"4f4ab8d65e04ca519482ed3d79dfdf6715d82fa7810fa3df5921031ede946abe","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-07T10:00:54Z","title_canon_sha256":"14d769bb1c7214e4fd1912def792ce645c6d0f8f75b16692473c7a2c4818ad50"},"schema_version":"1.0","source":{"id":"1809.02383","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.02383","created_at":"2026-07-05T02:08:57Z"},{"alias_kind":"arxiv_version","alias_value":"1809.02383v2","created_at":"2026-07-05T02:08:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.02383","created_at":"2026-07-05T02:08:57Z"},{"alias_kind":"pith_short_12","alias_value":"LD7GPCRYGUYG","created_at":"2026-07-05T02:08:57Z"},{"alias_kind":"pith_short_16","alias_value":"LD7GPCRYGUYGNCTV","created_at":"2026-07-05T02:08:57Z"},{"alias_kind":"pith_short_8","alias_value":"LD7GPCRY","created_at":"2026-07-05T02:08:57Z"}],"graph_snapshots":[{"event_id":"sha256:36502bc6600978a8ea662aac8e1bb7559463f51a80dc0436eb37a5c3ca91f3cc","target":"graph","created_at":"2026-07-05T02:08:57Z","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/1809.02383/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sensory data are often comprised of independent content and transformation factors. For example, face images may have shapes as content and poses as transformation. To infer separately these factors from given data, various ``disentangling'' models have been proposed. However, many of these are supervised or semi-supervised, either requiring attribute labels that are often unavailable or disallowing for generalization over new contents. In this study, we introduce a novel deep generative model, called group-based variational autoencoders. In this, we assume no explicit labels, but a weaker for","authors_text":"Haruo Hosoya","cross_cats":["cs.AI","cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-07T10:00:54Z","title":"Group-based Learning of Disentangled Representations with Generalizability for Novel Contents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.02383","kind":"arxiv","version":2},"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:c40d56cf47c0d1f3f651542c7b48f06a8e18d84e3d869afda446f48918c36b69","target":"record","created_at":"2026-07-05T02:08:57Z","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":"4f4ab8d65e04ca519482ed3d79dfdf6715d82fa7810fa3df5921031ede946abe","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-07T10:00:54Z","title_canon_sha256":"14d769bb1c7214e4fd1912def792ce645c6d0f8f75b16692473c7a2c4818ad50"},"schema_version":"1.0","source":{"id":"1809.02383","kind":"arxiv","version":2}},"canonical_sha256":"58fe678a383530668a754c6829e4630f90d79f9eb04edfeabd46f2ef71c768a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"58fe678a383530668a754c6829e4630f90d79f9eb04edfeabd46f2ef71c768a3","first_computed_at":"2026-07-05T02:08:57.409550Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:08:57.409550Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e+10mRekwSpo7OILRexo/zi+G9jR35uKLcLU8l2pJRrhTj2GtTExCBO6LixPB1M03nXFURVvepn94MNTH5DaBA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:08:57.409952Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.02383","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c40d56cf47c0d1f3f651542c7b48f06a8e18d84e3d869afda446f48918c36b69","sha256:36502bc6600978a8ea662aac8e1bb7559463f51a80dc0436eb37a5c3ca91f3cc"],"state_sha256":"7a6ed4c97f6a261fac56cfcf3009963274ebc32972a183b8285a93a6408572e6"}