{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:BF7NSBGJSXFRSC5FVOP2WZI2NW","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":"0c387a74a77fc05203b672edd9071638dab1a8ff4a171246c614ce720077ca53","cross_cats_sorted":["cs.CR","cs.PL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T13:23:02Z","title_canon_sha256":"7d3c0954e777431c66f9278522a1b5c2209f78279d375767842678e14a121df9"},"schema_version":"1.0","source":{"id":"2004.14756","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.14756","created_at":"2026-07-05T00:59:29Z"},{"alias_kind":"arxiv_version","alias_value":"2004.14756v1","created_at":"2026-07-05T00:59:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.14756","created_at":"2026-07-05T00:59:29Z"},{"alias_kind":"pith_short_12","alias_value":"BF7NSBGJSXFR","created_at":"2026-07-05T00:59:29Z"},{"alias_kind":"pith_short_16","alias_value":"BF7NSBGJSXFRSC5F","created_at":"2026-07-05T00:59:29Z"},{"alias_kind":"pith_short_8","alias_value":"BF7NSBGJ","created_at":"2026-07-05T00:59:29Z"}],"graph_snapshots":[{"event_id":"sha256:51ea056e6c07326074d0b65ce2b2139e737decd9872b14304fe92caeae3e4dc4","target":"graph","created_at":"2026-07-05T00:59:29Z","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/2004.14756/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative neural networks can be used to specify continuous transformations between images via latent-space interpolation. However, certifying that all images captured by the resulting path in the image manifold satisfy a given property can be very challenging. This is because this set is highly non-convex, thwarting existing scalable robustness analysis methods, which are often based on convex relaxations. We present ApproxLine, a scalable certification method that successfully verifies non-trivial specifications involving generative models and classifiers. ApproxLine can provide both sound ","authors_text":"Martin Vechev, Matthew Mirman, Timon Gehr","cross_cats":["cs.CR","cs.PL","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T13:23:02Z","title":"Robustness Certification of Generative Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.14756","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:b352c20efd212fcdf0f8ffbc184b156bcd7830910c1ced5883539e812167488d","target":"record","created_at":"2026-07-05T00:59:29Z","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":"0c387a74a77fc05203b672edd9071638dab1a8ff4a171246c614ce720077ca53","cross_cats_sorted":["cs.CR","cs.PL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T13:23:02Z","title_canon_sha256":"7d3c0954e777431c66f9278522a1b5c2209f78279d375767842678e14a121df9"},"schema_version":"1.0","source":{"id":"2004.14756","kind":"arxiv","version":1}},"canonical_sha256":"097ed904c995cb190ba5ab9fab651a6da9dd06bfe828970c8ab3b17fbfe1776e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"097ed904c995cb190ba5ab9fab651a6da9dd06bfe828970c8ab3b17fbfe1776e","first_computed_at":"2026-07-05T00:59:29.595800Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:59:29.595800Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nPRulk7SlbF+nzg8SGanh9XuRoZhXlN1cxvncVxUEYVk9f8TmkJOHrRL8sKuoZ+YCIdA5eMZPYoWZuuvCUqQCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:59:29.596208Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.14756","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b352c20efd212fcdf0f8ffbc184b156bcd7830910c1ced5883539e812167488d","sha256:51ea056e6c07326074d0b65ce2b2139e737decd9872b14304fe92caeae3e4dc4"],"state_sha256":"834ab12140adb5976e3d9a81a9e293893bc24c2b5268287319ee84431ef998a7"}