{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:J3Z5KW2LPROGVB7UDNC37PM2YE","short_pith_number":"pith:J3Z5KW2L","schema_version":"1.0","canonical_sha256":"4ef3d55b4b7c5c6a87f41b45bfbd9ac1353e86c0b6a12c9e5cf45612101085d9","source":{"kind":"arxiv","id":"2112.11561","version":5},"attestation_state":"computed","paper":{"title":"Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.AI","authors_text":"Hengshuai Yao, Mohammad Salameh, Randy Goebel, Shahin Atakishiyev","submitted_at":"2021-12-21T22:51:37Z","abstract_excerpt":"Autonomous driving has achieved significant milestones in research and development over the last two decades. There is increasing interest in the field as the deployment of autonomous vehicles (AVs) promises safer and more ecologically friendly transportation systems. With the rapid progress in computationally powerful artificial intelligence (AI) techniques, AVs can sense their environment with high precision, make safe real-time decisions, and operate reliably without human intervention. However, intelligent decision-making in such vehicles is not generally understandable by humans in the cu"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2112.11561","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2021-12-21T22:51:37Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"02801c7d0e8082296cd453580828aa6e5b14c9815ed0da6209bc8dedb69e9472","abstract_canon_sha256":"43c03eaf41d1b87f6c753ea4d9c52fc497d6fa501011521809fb91f45edf7224"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:13.194408Z","signature_b64":"Bj3q8m5T94SoJ4sZ1PJeZdU9EEi7i4GrQX4Vj8p309APJsoqkETqdU89tJRIts8CgwPClOuZK6F1/pTu8QwqAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ef3d55b4b7c5c6a87f41b45bfbd9ac1353e86c0b6a12c9e5cf45612101085d9","last_reissued_at":"2026-07-05T08:12:13.193973Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:13.193973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.AI","authors_text":"Hengshuai Yao, Mohammad Salameh, Randy Goebel, Shahin Atakishiyev","submitted_at":"2021-12-21T22:51:37Z","abstract_excerpt":"Autonomous driving has achieved significant milestones in research and development over the last two decades. There is increasing interest in the field as the deployment of autonomous vehicles (AVs) promises safer and more ecologically friendly transportation systems. With the rapid progress in computationally powerful artificial intelligence (AI) techniques, AVs can sense their environment with high precision, make safe real-time decisions, and operate reliably without human intervention. However, intelligent decision-making in such vehicles is not generally understandable by humans in the cu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.11561","kind":"arxiv","version":5},"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/2112.11561/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2112.11561","created_at":"2026-07-05T08:12:13.194033+00:00"},{"alias_kind":"arxiv_version","alias_value":"2112.11561v5","created_at":"2026-07-05T08:12:13.194033+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.11561","created_at":"2026-07-05T08:12:13.194033+00:00"},{"alias_kind":"pith_short_12","alias_value":"J3Z5KW2LPROG","created_at":"2026-07-05T08:12:13.194033+00:00"},{"alias_kind":"pith_short_16","alias_value":"J3Z5KW2LPROGVB7U","created_at":"2026-07-05T08:12:13.194033+00:00"},{"alias_kind":"pith_short_8","alias_value":"J3Z5KW2L","created_at":"2026-07-05T08:12:13.194033+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.05461","citing_title":"Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety","ref_index":1,"is_internal_anchor":false},{"citing_arxiv_id":"2605.21446","citing_title":"Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs","ref_index":1,"is_internal_anchor":false},{"citing_arxiv_id":"2605.21446","citing_title":"Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs","ref_index":1,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE","json":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE.json","graph_json":"https://pith.science/api/pith-number/J3Z5KW2LPROGVB7UDNC37PM2YE/graph.json","events_json":"https://pith.science/api/pith-number/J3Z5KW2LPROGVB7UDNC37PM2YE/events.json","paper":"https://pith.science/paper/J3Z5KW2L"},"agent_actions":{"view_html":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE","download_json":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE.json","view_paper":"https://pith.science/paper/J3Z5KW2L","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2112.11561&json=true","fetch_graph":"https://pith.science/api/pith-number/J3Z5KW2LPROGVB7UDNC37PM2YE/graph.json","fetch_events":"https://pith.science/api/pith-number/J3Z5KW2LPROGVB7UDNC37PM2YE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE/action/storage_attestation","attest_author":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE/action/author_attestation","sign_citation":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE/action/citation_signature","submit_replication":"https://pith.science/pith/J3Z5KW2LPROGVB7UDNC37PM2YE/action/replication_record"}},"created_at":"2026-07-05T08:12:13.194033+00:00","updated_at":"2026-07-05T08:12:13.194033+00:00"}