{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:LWG2QY4G3WY6X34BVWNZNQ6UEG","short_pith_number":"pith:LWG2QY4G","canonical_record":{"source":{"id":"1708.08296","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-28T12:53:49Z","cross_cats_sorted":["cs.CY","cs.NE","stat.ML"],"title_canon_sha256":"1daff487a394db50c700fd5ef4594531fdbd99b842dbe00b5fb4af2d1005c42a","abstract_canon_sha256":"2b943e99028aa9fb4a179205513601fb327d323c8695152df8ad7540a4f3dcba"},"schema_version":"1.0"},"canonical_sha256":"5d8da86386ddb1ebef81ad9b96c3d4218f545fd4c8484ca811cb4e73cbda7ef4","source":{"kind":"arxiv","id":"1708.08296","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.08296","created_at":"2026-05-18T00:36:36Z"},{"alias_kind":"arxiv_version","alias_value":"1708.08296v1","created_at":"2026-05-18T00:36:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.08296","created_at":"2026-05-18T00:36:36Z"},{"alias_kind":"pith_short_12","alias_value":"LWG2QY4G3WY6","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LWG2QY4G3WY6X34B","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LWG2QY4G","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:LWG2QY4G3WY6X34BVWNZNQ6UEG","target":"record","payload":{"canonical_record":{"source":{"id":"1708.08296","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-28T12:53:49Z","cross_cats_sorted":["cs.CY","cs.NE","stat.ML"],"title_canon_sha256":"1daff487a394db50c700fd5ef4594531fdbd99b842dbe00b5fb4af2d1005c42a","abstract_canon_sha256":"2b943e99028aa9fb4a179205513601fb327d323c8695152df8ad7540a4f3dcba"},"schema_version":"1.0"},"canonical_sha256":"5d8da86386ddb1ebef81ad9b96c3d4218f545fd4c8484ca811cb4e73cbda7ef4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:36:36.453624Z","signature_b64":"uy9mhOhwL4VMm5zmHW+UWlTJcIIOJxXE4l2Tl+MqxFH0Sa5rSfSacgD1UBonltZKRcTT8Fr0gMVF+HduFpXFDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d8da86386ddb1ebef81ad9b96c3d4218f545fd4c8484ca811cb4e73cbda7ef4","last_reissued_at":"2026-05-18T00:36:36.453135Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:36:36.453135Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.08296","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":"2026-05-18T00:36:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L1qHN9sFfNw3O/3ibmqHiDcGjUbA7Z2C681fA0oPtm5ebp/Ysu9GK1vq/rEuFFckKRwlQIgPnk36EQolybvlBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T19:16:34.697643Z"},"content_sha256":"4cdf0c05b7edb2bdd6ffc62dd22eaa1ba6e02819d5dc308d8aa937eeb9724b1b","schema_version":"1.0","event_id":"sha256:4cdf0c05b7edb2bdd6ffc62dd22eaa1ba6e02819d5dc308d8aa937eeb9724b1b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:LWG2QY4G3WY6X34BVWNZNQ6UEG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CY","cs.NE","stat.ML"],"primary_cat":"cs.AI","authors_text":"Klaus-Robert M\\\"uller, Thomas Wiegand, Wojciech Samek","submitted_at":"2017-08-28T12:53:49Z","abstract_excerpt":"With the availability of large databases and recent improvements in deep learning methodology, the performance of AI systems is reaching or even exceeding the human level on an increasing number of complex tasks. Impressive examples of this development can be found in domains such as image classification, sentiment analysis, speech understanding or strategic game playing. However, because of their nested non-linear structure, these highly successful machine learning and artificial intelligence models are usually applied in a black box manner, i.e., no information is provided about what exactly"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.08296","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":""},"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":"2026-05-18T00:36:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qtDxhI3/NixHYSr3W9BSulH7y/5tS8ZAyer5IJaL51n6OBKkNQuc4lKPEC73TqZC4TLwhNosHxNXH5YoYeFpAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T19:16:34.698006Z"},"content_sha256":"4eaffc24ecb5d897decbe2646e9a00b1055308c203f50bd24f32fbc003178ecf","schema_version":"1.0","event_id":"sha256:4eaffc24ecb5d897decbe2646e9a00b1055308c203f50bd24f32fbc003178ecf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG/bundle.json","state_url":"https://pith.science/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG/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":"2026-05-31T19:16:34Z","links":{"resolver":"https://pith.science/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG","bundle":"https://pith.science/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG/bundle.json","state":"https://pith.science/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LWG2QY4G3WY6X34BVWNZNQ6UEG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LWG2QY4G3WY6X34BVWNZNQ6UEG","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":"2b943e99028aa9fb4a179205513601fb327d323c8695152df8ad7540a4f3dcba","cross_cats_sorted":["cs.CY","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-28T12:53:49Z","title_canon_sha256":"1daff487a394db50c700fd5ef4594531fdbd99b842dbe00b5fb4af2d1005c42a"},"schema_version":"1.0","source":{"id":"1708.08296","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.08296","created_at":"2026-05-18T00:36:36Z"},{"alias_kind":"arxiv_version","alias_value":"1708.08296v1","created_at":"2026-05-18T00:36:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.08296","created_at":"2026-05-18T00:36:36Z"},{"alias_kind":"pith_short_12","alias_value":"LWG2QY4G3WY6","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LWG2QY4G3WY6X34B","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LWG2QY4G","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:4eaffc24ecb5d897decbe2646e9a00b1055308c203f50bd24f32fbc003178ecf","target":"graph","created_at":"2026-05-18T00:36:36Z","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"},"paper":{"abstract_excerpt":"With the availability of large databases and recent improvements in deep learning methodology, the performance of AI systems is reaching or even exceeding the human level on an increasing number of complex tasks. Impressive examples of this development can be found in domains such as image classification, sentiment analysis, speech understanding or strategic game playing. However, because of their nested non-linear structure, these highly successful machine learning and artificial intelligence models are usually applied in a black box manner, i.e., no information is provided about what exactly","authors_text":"Klaus-Robert M\\\"uller, Thomas Wiegand, Wojciech Samek","cross_cats":["cs.CY","cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-28T12:53:49Z","title":"Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.08296","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":"sha256:4cdf0c05b7edb2bdd6ffc62dd22eaa1ba6e02819d5dc308d8aa937eeb9724b1b","target":"record","created_at":"2026-05-18T00:36:36Z","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":"2b943e99028aa9fb4a179205513601fb327d323c8695152df8ad7540a4f3dcba","cross_cats_sorted":["cs.CY","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-28T12:53:49Z","title_canon_sha256":"1daff487a394db50c700fd5ef4594531fdbd99b842dbe00b5fb4af2d1005c42a"},"schema_version":"1.0","source":{"id":"1708.08296","kind":"arxiv","version":1}},"canonical_sha256":"5d8da86386ddb1ebef81ad9b96c3d4218f545fd4c8484ca811cb4e73cbda7ef4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d8da86386ddb1ebef81ad9b96c3d4218f545fd4c8484ca811cb4e73cbda7ef4","first_computed_at":"2026-05-18T00:36:36.453135Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:36:36.453135Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uy9mhOhwL4VMm5zmHW+UWlTJcIIOJxXE4l2Tl+MqxFH0Sa5rSfSacgD1UBonltZKRcTT8Fr0gMVF+HduFpXFDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:36:36.453624Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.08296","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4cdf0c05b7edb2bdd6ffc62dd22eaa1ba6e02819d5dc308d8aa937eeb9724b1b","sha256:4eaffc24ecb5d897decbe2646e9a00b1055308c203f50bd24f32fbc003178ecf"],"state_sha256":"da00d60d4d4b5c177ac6890368f915ec522db87f0a17121db9f04fbef19a94ce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wgU7Oss4NXtF6Qi3540GGvPor2IZeLNUHNxKRDA/VDQH3oeIiAelhXoP5BejV8sZpOgtUhvmkq/j3G6QEA1AAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T19:16:34.700106Z","bundle_sha256":"d1573126f0c153f2c52e6f96a0f207a3a015b3b2d6ccee0ae8b987bbcc487c0d"}}