{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:3M22GA5OOGILYLIGJAK2OWSVGL","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":"a68a9849b576bd8ec777ed52488fc5130b9e2ec041f5e0ceb35411c94542f78d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-16T02:58:10Z","title_canon_sha256":"96138595faa8ccf3cba91194ce48682ccb6b2dd59f634eb9db827fdf29b7c25d"},"schema_version":"1.0","source":{"id":"2006.11371","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.11371","created_at":"2026-07-05T01:12:03Z"},{"alias_kind":"arxiv_version","alias_value":"2006.11371v2","created_at":"2026-07-05T01:12:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.11371","created_at":"2026-07-05T01:12:03Z"},{"alias_kind":"pith_short_12","alias_value":"3M22GA5OOGIL","created_at":"2026-07-05T01:12:03Z"},{"alias_kind":"pith_short_16","alias_value":"3M22GA5OOGILYLIG","created_at":"2026-07-05T01:12:03Z"},{"alias_kind":"pith_short_8","alias_value":"3M22GA5O","created_at":"2026-07-05T01:12:03Z"}],"graph_snapshots":[{"event_id":"sha256:dc585b6c7d13dcf88ccf0ddb4b75cd9a91651a04991d6fdc4a576e842508d3bd","target":"graph","created_at":"2026-07-05T01:12:03Z","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/2006.11371/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Nowadays, deep neural networks are widely used in mission critical systems such as healthcare, self-driving vehicles, and military which have direct impact on human lives. However, the black-box nature of deep neural networks challenges its use in mission critical applications, raising ethical and judicial concerns inducing lack of trust. Explainable Artificial Intelligence (XAI) is a field of Artificial Intelligence (AI) that promotes a set of tools, techniques, and algorithms that can generate high-quality interpretable, intuitive, human-understandable explanations of AI decisions. In additi","authors_text":"Arun Das, Paul Rad","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-16T02:58:10Z","title":"Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.11371","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":"sha256:732f8e1ff5e99107f505624a04a651572a71e3ff1b766da4337170407d863a7b","target":"record","created_at":"2026-07-05T01:12:03Z","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":"a68a9849b576bd8ec777ed52488fc5130b9e2ec041f5e0ceb35411c94542f78d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-16T02:58:10Z","title_canon_sha256":"96138595faa8ccf3cba91194ce48682ccb6b2dd59f634eb9db827fdf29b7c25d"},"schema_version":"1.0","source":{"id":"2006.11371","kind":"arxiv","version":2}},"canonical_sha256":"db35a303ae7190bc2d064815a75a5532e522ee2e80adb48bbe6365b908df6261","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db35a303ae7190bc2d064815a75a5532e522ee2e80adb48bbe6365b908df6261","first_computed_at":"2026-07-05T01:12:03.296617Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:12:03.296617Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XOsi1pqSPNXl3G3N8Wzh7EtCGAiuI+4GmduZhEMV3PGtyD9tB4BwmccWYqNdvgIAGe8Hkwcywrkj+Vpa+R9RCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:12:03.297108Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.11371","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:732f8e1ff5e99107f505624a04a651572a71e3ff1b766da4337170407d863a7b","sha256:dc585b6c7d13dcf88ccf0ddb4b75cd9a91651a04991d6fdc4a576e842508d3bd"],"state_sha256":"0db864b5ca5f464eb96ddc8dc3c86d37230e6cc00a52a8b2b4ceab23d11946c6"}