{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:SMOV4GOT7YAINYN5L5I5TWCNH7","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":"3d21a8c2ba52da7345597c3ddcd79f9db451b49e35b6034c53675772be1f24cc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-11-17T13:20:29Z","title_canon_sha256":"4874e3221f0b89b35cb53d460ad839d27eda4f3d0fa772a402f4187abbc33e53"},"schema_version":"1.0","source":{"id":"2111.09094","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.09094","created_at":"2026-07-05T04:41:10Z"},{"alias_kind":"arxiv_version","alias_value":"2111.09094v3","created_at":"2026-07-05T04:41:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.09094","created_at":"2026-07-05T04:41:10Z"},{"alias_kind":"pith_short_12","alias_value":"SMOV4GOT7YAI","created_at":"2026-07-05T04:41:10Z"},{"alias_kind":"pith_short_16","alias_value":"SMOV4GOT7YAINYN5","created_at":"2026-07-05T04:41:10Z"},{"alias_kind":"pith_short_8","alias_value":"SMOV4GOT","created_at":"2026-07-05T04:41:10Z"}],"graph_snapshots":[{"event_id":"sha256:71f8e018862a2ab1e890aa4d47df6fd1ba52446cd7d2ad4a8a3b2a1a59616e14","target":"graph","created_at":"2026-07-05T04:41:10Z","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/2111.09094/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As deep learning models are increasingly used in safety-critical applications, explainability and trustworthiness become major concerns. For simple images, such as low-resolution face portraits, synthesizing visual counterfactual explanations has recently been proposed as a way to uncover the decision mechanisms of a trained classification model. In this work, we address the problem of producing counterfactual explanations for high-quality images and complex scenes. Leveraging recent semantic-to-image models, we propose a new generative counterfactual explanation framework that produces plausi","authors_text":"\\'Eloi Zablocki, H\\'edi Ben-Younes, Matthieu Cord, Micka\\\"el Chen, Patrick P\\'erez, Paul Jacob","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-11-17T13:20:29Z","title":"STEEX: Steering Counterfactual Explanations with Semantics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.09094","kind":"arxiv","version":3},"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":"sha256:275c7719eca945da07732535613e21f36ca5cf5a98ddb2942a981a2743799ff6","target":"record","created_at":"2026-07-05T04:41:10Z","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":"3d21a8c2ba52da7345597c3ddcd79f9db451b49e35b6034c53675772be1f24cc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2021-11-17T13:20:29Z","title_canon_sha256":"4874e3221f0b89b35cb53d460ad839d27eda4f3d0fa772a402f4187abbc33e53"},"schema_version":"1.0","source":{"id":"2111.09094","kind":"arxiv","version":3}},"canonical_sha256":"931d5e19d3fe0086e1bd5f51d9d84d3fc2ca2d116a7550046f764963d55704af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"931d5e19d3fe0086e1bd5f51d9d84d3fc2ca2d116a7550046f764963d55704af","first_computed_at":"2026-07-05T04:41:10.622470Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:41:10.622470Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CVcyigZy2E0ussqHzwp7lwX7eoYrbeWvASWmXLVx/n7y+VXj84l2M8ElDmQ0GHux84+/BQt1EFnD7fJkF3wnBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:41:10.622951Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.09094","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:275c7719eca945da07732535613e21f36ca5cf5a98ddb2942a981a2743799ff6","sha256:71f8e018862a2ab1e890aa4d47df6fd1ba52446cd7d2ad4a8a3b2a1a59616e14"],"state_sha256":"135170f88ed1ab528e6f10d506bfe54b7366f3ae6d308ab58194f64affd1dda0"}