{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:WBF2LBSSV34IE6533V52Z7ERQ4","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":"c79dd4fb20a269d1b7adcba72dfa89a779b58148c4f5c2421fd592f8270d3e75","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T13:16:18Z","title_canon_sha256":"126ac904c7ea33de8270bf24e59b8084991f32ff5cb0f93df03775aef72424f8"},"schema_version":"1.0","source":{"id":"2202.00391","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.00391","created_at":"2026-07-05T03:53:21Z"},{"alias_kind":"arxiv_version","alias_value":"2202.00391v1","created_at":"2026-07-05T03:53:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.00391","created_at":"2026-07-05T03:53:21Z"},{"alias_kind":"pith_short_12","alias_value":"WBF2LBSSV34I","created_at":"2026-07-05T03:53:21Z"},{"alias_kind":"pith_short_16","alias_value":"WBF2LBSSV34IE653","created_at":"2026-07-05T03:53:21Z"},{"alias_kind":"pith_short_8","alias_value":"WBF2LBSS","created_at":"2026-07-05T03:53:21Z"}],"graph_snapshots":[{"event_id":"sha256:0bdb0164355b862a5c97e05847e64763578656381f5efb417c19cb26c1caca83","target":"graph","created_at":"2026-07-05T03:53:21Z","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/2202.00391/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A key assumption of most statistical machine learning methods is that they have access to independent samples from the distribution of data they encounter at test time. As such, these methods often perform poorly in the face of biased data, which breaks this assumption. In particular, machine learning models have been shown to exhibit Clever-Hans-like behaviour, meaning that spurious correlations in the training set are inadvertently learnt. A number of works have been proposed to revise deep classifiers to learn the right correlations. However, generative models have been overlooked so far. W","authors_text":"Karl Stelzner, Kristian Kersting, Xiaoting Shao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T13:16:18Z","title":"Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.00391","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:a477a1b8205d6e48130f7b2b509a055dadd493da7b072d7ea3feb2a729d62174","target":"record","created_at":"2026-07-05T03:53:21Z","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":"c79dd4fb20a269d1b7adcba72dfa89a779b58148c4f5c2421fd592f8270d3e75","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T13:16:18Z","title_canon_sha256":"126ac904c7ea33de8270bf24e59b8084991f32ff5cb0f93df03775aef72424f8"},"schema_version":"1.0","source":{"id":"2202.00391","kind":"arxiv","version":1}},"canonical_sha256":"b04ba58652aef8827bbbdd7bacfc91870722171dc664bc448adef53057cd1de9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b04ba58652aef8827bbbdd7bacfc91870722171dc664bc448adef53057cd1de9","first_computed_at":"2026-07-05T03:53:21.600790Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:53:21.600790Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"srJR2jpGyv2SWNiOvZ2HmAEa5Zmci0mc365PrSnnaWj9I9aLVMgIUx5O5MroTMAsfLzc+5IZrfzl8ATPMoU3Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:53:21.601311Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.00391","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a477a1b8205d6e48130f7b2b509a055dadd493da7b072d7ea3feb2a729d62174","sha256:0bdb0164355b862a5c97e05847e64763578656381f5efb417c19cb26c1caca83"],"state_sha256":"f8c777f113d0996694c635d9029df1ef857a1afa2188ab76b210ed5dced21cff"}