{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:M2LREJXO7RZHKL5LPZIM4ZFMD5","short_pith_number":"pith:M2LREJXO","canonical_record":{"source":{"id":"2207.07553","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-15T15:51:08Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"d6d349c09613bf0955cd1a2f587fc6613dced047aa393cf1c9b8b95737f2b79f","abstract_canon_sha256":"091da56687bc5622b6799bb6ad6c532013e67fd0b6568222bb0fc7f90322c183"},"schema_version":"1.0"},"canonical_sha256":"66971226eefc72752fab7e50ce64ac1f559aa6d4ecf3533483ee1bb654dd72f0","source":{"kind":"arxiv","id":"2207.07553","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.07553","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"arxiv_version","alias_value":"2207.07553v1","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.07553","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"pith_short_12","alias_value":"M2LREJXO7RZH","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"pith_short_16","alias_value":"M2LREJXO7RZHKL5L","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"pith_short_8","alias_value":"M2LREJXO","created_at":"2026-07-05T04:40:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:M2LREJXO7RZHKL5LPZIM4ZFMD5","target":"record","payload":{"canonical_record":{"source":{"id":"2207.07553","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-15T15:51:08Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"d6d349c09613bf0955cd1a2f587fc6613dced047aa393cf1c9b8b95737f2b79f","abstract_canon_sha256":"091da56687bc5622b6799bb6ad6c532013e67fd0b6568222bb0fc7f90322c183"},"schema_version":"1.0"},"canonical_sha256":"66971226eefc72752fab7e50ce64ac1f559aa6d4ecf3533483ee1bb654dd72f0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:40:33.745105Z","signature_b64":"+a6rwOpUsv8G6r1EJIrSMj02aVGnB21Vfyjvv5Y5ccd76AAjnXNezdu1oqqPEIoKjG6c8CaynQbGaxvM+uF5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66971226eefc72752fab7e50ce64ac1f559aa6d4ecf3533483ee1bb654dd72f0","last_reissued_at":"2026-07-05T04:40:33.744625Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:40:33.744625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.07553","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:40:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZN3P4V1FMbcwTB1Sxz/DU41cO7q+AKsUbmx/tDYheIxvCisiOlJdSpyvB6ahA+P6sMHOiwuLa+IU6rmp2pNDCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T23:52:56.242420Z"},"content_sha256":"02d385700ada49695db30aa6088f40667b25eaa3046e99d601f6056513b9fb97","schema_version":"1.0","event_id":"sha256:02d385700ada49695db30aa6088f40667b25eaa3046e99d601f6056513b9fb97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:M2LREJXO7RZHKL5LPZIM4ZFMD5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Ashkan Khakzar, Bene Wiestler, Jan Kirschke, Matan Atad, Matthias Keicher, Nassir Navab, Vitalii Dmytrenko, Xinyue Zhang, Yitong Li","submitted_at":"2022-07-15T15:51:08Z","abstract_excerpt":"Deep learning models used in medical image analysis are prone to raising reliability concerns due to their black-box nature. To shed light on these black-box models, previous works predominantly focus on identifying the contribution of input features to the diagnosis, i.e., feature attribution. In this work, we explore counterfactual explanations to identify what patterns the models rely on for diagnosis. Specifically, we investigate the effect of changing features within chest X-rays on the classifier's output to understand its decision mechanism. We leverage a StyleGAN-based approach (StyleE"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.07553","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.07553/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:40:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ASDDN2Y/dDwmZeTovYF1McO40JynZA3p7mmI1LTEhD79E+5BjlvwF8xtZlOy5l/uIeXzUpzDr2AbYaz4+gjeAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T23:52:56.243001Z"},"content_sha256":"39a3ce238cbf0fda2b5a6bcd533eac178d0dc9c1491b5f0c625c22d01c3f5f3f","schema_version":"1.0","event_id":"sha256:39a3ce238cbf0fda2b5a6bcd533eac178d0dc9c1491b5f0c625c22d01c3f5f3f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5/bundle.json","state_url":"https://pith.science/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T23:52:56Z","links":{"resolver":"https://pith.science/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5","bundle":"https://pith.science/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5/bundle.json","state":"https://pith.science/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M2LREJXO7RZHKL5LPZIM4ZFMD5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:M2LREJXO7RZHKL5LPZIM4ZFMD5","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":"091da56687bc5622b6799bb6ad6c532013e67fd0b6568222bb0fc7f90322c183","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-15T15:51:08Z","title_canon_sha256":"d6d349c09613bf0955cd1a2f587fc6613dced047aa393cf1c9b8b95737f2b79f"},"schema_version":"1.0","source":{"id":"2207.07553","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.07553","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"arxiv_version","alias_value":"2207.07553v1","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.07553","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"pith_short_12","alias_value":"M2LREJXO7RZH","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"pith_short_16","alias_value":"M2LREJXO7RZHKL5L","created_at":"2026-07-05T04:40:33Z"},{"alias_kind":"pith_short_8","alias_value":"M2LREJXO","created_at":"2026-07-05T04:40:33Z"}],"graph_snapshots":[{"event_id":"sha256:39a3ce238cbf0fda2b5a6bcd533eac178d0dc9c1491b5f0c625c22d01c3f5f3f","target":"graph","created_at":"2026-07-05T04:40:33Z","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/2207.07553/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning models used in medical image analysis are prone to raising reliability concerns due to their black-box nature. To shed light on these black-box models, previous works predominantly focus on identifying the contribution of input features to the diagnosis, i.e., feature attribution. In this work, we explore counterfactual explanations to identify what patterns the models rely on for diagnosis. Specifically, we investigate the effect of changing features within chest X-rays on the classifier's output to understand its decision mechanism. We leverage a StyleGAN-based approach (StyleE","authors_text":"Ashkan Khakzar, Bene Wiestler, Jan Kirschke, Matan Atad, Matthias Keicher, Nassir Navab, Vitalii Dmytrenko, Xinyue Zhang, Yitong Li","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-15T15:51:08Z","title":"CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.07553","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":"sha256:02d385700ada49695db30aa6088f40667b25eaa3046e99d601f6056513b9fb97","target":"record","created_at":"2026-07-05T04:40:33Z","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":"091da56687bc5622b6799bb6ad6c532013e67fd0b6568222bb0fc7f90322c183","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-07-15T15:51:08Z","title_canon_sha256":"d6d349c09613bf0955cd1a2f587fc6613dced047aa393cf1c9b8b95737f2b79f"},"schema_version":"1.0","source":{"id":"2207.07553","kind":"arxiv","version":1}},"canonical_sha256":"66971226eefc72752fab7e50ce64ac1f559aa6d4ecf3533483ee1bb654dd72f0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66971226eefc72752fab7e50ce64ac1f559aa6d4ecf3533483ee1bb654dd72f0","first_computed_at":"2026-07-05T04:40:33.744625Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:40:33.744625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+a6rwOpUsv8G6r1EJIrSMj02aVGnB21Vfyjvv5Y5ccd76AAjnXNezdu1oqqPEIoKjG6c8CaynQbGaxvM+uF5DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:40:33.745105Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.07553","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:02d385700ada49695db30aa6088f40667b25eaa3046e99d601f6056513b9fb97","sha256:39a3ce238cbf0fda2b5a6bcd533eac178d0dc9c1491b5f0c625c22d01c3f5f3f"],"state_sha256":"43f5fe844e867147fe9db33c0d02d6834474aa59e38ad077f0f18e0c131591a1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GubyP8nKUQPE+zKmP1flUpLGmCQSCECEt15GP9PLhD1dzBFln7L4n9VyVPLBU5qI3rhwYeTbNAMLXmuvLO5WAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T23:52:56.246497Z","bundle_sha256":"e2c8b151a5df8b98b56fedc1d1f14cec541e4ad3b772995e2534c37b39b0d72c"}}