{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KF6E47QBRXWPN7OLOZH4BCKBJG","short_pith_number":"pith:KF6E47QB","canonical_record":{"source":{"id":"2206.03208","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-07T12:05:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e8c5c07b7c0b099fda509a2f3fbc096009b6d24720c4d694ad14d6f1f8f5afbd","abstract_canon_sha256":"b59903084646210103272078920931b8fa4c4fc241fabca878e76216b4532011"},"schema_version":"1.0"},"canonical_sha256":"517c4e7e018decf6fdcb764fc08941498c40daed00d98c7aeccb49443ad7a4b0","source":{"kind":"arxiv","id":"2206.03208","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.03208","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"arxiv_version","alias_value":"2206.03208v2","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.03208","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"pith_short_12","alias_value":"KF6E47QBRXWP","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"pith_short_16","alias_value":"KF6E47QBRXWPN7OL","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"pith_short_8","alias_value":"KF6E47QB","created_at":"2026-07-05T07:30:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KF6E47QBRXWPN7OLOZH4BCKBJG","target":"record","payload":{"canonical_record":{"source":{"id":"2206.03208","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-07T12:05:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e8c5c07b7c0b099fda509a2f3fbc096009b6d24720c4d694ad14d6f1f8f5afbd","abstract_canon_sha256":"b59903084646210103272078920931b8fa4c4fc241fabca878e76216b4532011"},"schema_version":"1.0"},"canonical_sha256":"517c4e7e018decf6fdcb764fc08941498c40daed00d98c7aeccb49443ad7a4b0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:30:43.774788Z","signature_b64":"mqhKQrsgLewYYTAZSM3S4ezybloszocVG117xgEpGoRFpNUZgYUJQnkXH7KsEFDsNRJIyXdq4Nvem/4VBp2CDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"517c4e7e018decf6fdcb764fc08941498c40daed00d98c7aeccb49443ad7a4b0","last_reissued_at":"2026-07-05T07:30:43.774293Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:30:43.774293Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.03208","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:30:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oYvjOERhNhcXtN+VqNR+ibEvTsdFdpXt6/QGig1nydrVcVkZldLGMHkjDRK1pr7a1A1WEWYmTJs2N22vci80Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T00:17:28.247547Z"},"content_sha256":"9b9f7226a739b059aa44498c527f57c6c0aa42f8ba246e098203e0039cc1df17","schema_version":"1.0","event_id":"sha256:9b9f7226a739b059aa44498c527f57c6c0aa42f8ba246e098203e0039cc1df17"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KF6E47QBRXWPN7OLOZH4BCKBJG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Ilona Eisenbraun, Maximilian Dreyer, Reduan Achtibat, Sebastian Bosse, Sebastian Lapuschkin, Thomas Wiegand, Wojciech Samek","submitted_at":"2022-06-07T12:05:58Z","abstract_excerpt":"The field of eXplainable Artificial Intelligence (XAI) aims to bring transparency to today's powerful but opaque deep learning models. While local XAI methods explain individual predictions in form of attribution maps, thereby identifying where important features occur (but not providing information about what they represent), global explanation techniques visualize what concepts a model has generally learned to encode. Both types of methods thus only provide partial insights and leave the burden of interpreting the model's reasoning to the user. In this work we introduce the Concept Relevance"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.03208","kind":"arxiv","version":2},"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/2206.03208/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":"2026-07-05T07:30:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RlQ6InaWf+7uu4vyouLE75ILVSGueV/+1nWiBM60ht8+3oqOIcEGrA+UDwL9B4DF2sBdqPmz5XO6gu4mlQiaCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T00:17:28.255109Z"},"content_sha256":"a7836e2f8c9d9af83275c2a4783ab2245ead4a04dd416a3a76617ad3149ac4f5","schema_version":"1.0","event_id":"sha256:a7836e2f8c9d9af83275c2a4783ab2245ead4a04dd416a3a76617ad3149ac4f5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KF6E47QBRXWPN7OLOZH4BCKBJG/bundle.json","state_url":"https://pith.science/pith/KF6E47QBRXWPN7OLOZH4BCKBJG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KF6E47QBRXWPN7OLOZH4BCKBJG/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":"2026-08-14T00:17:28Z","links":{"resolver":"https://pith.science/pith/KF6E47QBRXWPN7OLOZH4BCKBJG","bundle":"https://pith.science/pith/KF6E47QBRXWPN7OLOZH4BCKBJG/bundle.json","state":"https://pith.science/pith/KF6E47QBRXWPN7OLOZH4BCKBJG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KF6E47QBRXWPN7OLOZH4BCKBJG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KF6E47QBRXWPN7OLOZH4BCKBJG","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":"b59903084646210103272078920931b8fa4c4fc241fabca878e76216b4532011","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-07T12:05:58Z","title_canon_sha256":"e8c5c07b7c0b099fda509a2f3fbc096009b6d24720c4d694ad14d6f1f8f5afbd"},"schema_version":"1.0","source":{"id":"2206.03208","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.03208","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"arxiv_version","alias_value":"2206.03208v2","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.03208","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"pith_short_12","alias_value":"KF6E47QBRXWP","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"pith_short_16","alias_value":"KF6E47QBRXWPN7OL","created_at":"2026-07-05T07:30:43Z"},{"alias_kind":"pith_short_8","alias_value":"KF6E47QB","created_at":"2026-07-05T07:30:43Z"}],"graph_snapshots":[{"event_id":"sha256:a7836e2f8c9d9af83275c2a4783ab2245ead4a04dd416a3a76617ad3149ac4f5","target":"graph","created_at":"2026-07-05T07:30:43Z","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/2206.03208/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The field of eXplainable Artificial Intelligence (XAI) aims to bring transparency to today's powerful but opaque deep learning models. While local XAI methods explain individual predictions in form of attribution maps, thereby identifying where important features occur (but not providing information about what they represent), global explanation techniques visualize what concepts a model has generally learned to encode. Both types of methods thus only provide partial insights and leave the burden of interpreting the model's reasoning to the user. In this work we introduce the Concept Relevance","authors_text":"Ilona Eisenbraun, Maximilian Dreyer, Reduan Achtibat, Sebastian Bosse, Sebastian Lapuschkin, Thomas Wiegand, Wojciech Samek","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-07T12:05:58Z","title":"From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.03208","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":"sha256:9b9f7226a739b059aa44498c527f57c6c0aa42f8ba246e098203e0039cc1df17","target":"record","created_at":"2026-07-05T07:30:43Z","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":"b59903084646210103272078920931b8fa4c4fc241fabca878e76216b4532011","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-07T12:05:58Z","title_canon_sha256":"e8c5c07b7c0b099fda509a2f3fbc096009b6d24720c4d694ad14d6f1f8f5afbd"},"schema_version":"1.0","source":{"id":"2206.03208","kind":"arxiv","version":2}},"canonical_sha256":"517c4e7e018decf6fdcb764fc08941498c40daed00d98c7aeccb49443ad7a4b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"517c4e7e018decf6fdcb764fc08941498c40daed00d98c7aeccb49443ad7a4b0","first_computed_at":"2026-07-05T07:30:43.774293Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:30:43.774293Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mqhKQrsgLewYYTAZSM3S4ezybloszocVG117xgEpGoRFpNUZgYUJQnkXH7KsEFDsNRJIyXdq4Nvem/4VBp2CDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:30:43.774788Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.03208","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9b9f7226a739b059aa44498c527f57c6c0aa42f8ba246e098203e0039cc1df17","sha256:a7836e2f8c9d9af83275c2a4783ab2245ead4a04dd416a3a76617ad3149ac4f5"],"state_sha256":"86e38729e59905eabf2db572af16d411e2a7b7e87dd9e475300987b76ba4bd4c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0Bg1emD7q0XphFH+rd7PU1abh919BNd0HIryxpJeNCbgWznA8WsKGQcyNk+KU/TJjPzAada8LmUKe7OuqeV3AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T00:17:28.268739Z","bundle_sha256":"e288dcadf280e660f16c6d8da73c3a320c0fe7edeb2db8692a336342c144f934"}}