{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:BD73KWXLHU6I4RXRVXM7LFIGN3","short_pith_number":"pith:BD73KWXL","canonical_record":{"source":{"id":"2605.16087","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-15T15:47:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ddd5e74aaf1824137518e8e0cb05519e581c345362cac92786b3329948660e82","abstract_canon_sha256":"10d5a9d087627af402f2d8d2ef828392af3433fadfe6d07e3a62b0e8cdbff9ad"},"schema_version":"1.0"},"canonical_sha256":"08ffb55aeb3d3c8e46f1add9f595066eec2f5e4ddfdca94344f41ba6ac350174","source":{"kind":"arxiv","id":"2605.16087","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16087","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16087v1","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16087","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"pith_short_12","alias_value":"BD73KWXLHU6I","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"pith_short_16","alias_value":"BD73KWXLHU6I4RXR","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"pith_short_8","alias_value":"BD73KWXL","created_at":"2026-05-20T00:01:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:BD73KWXLHU6I4RXRVXM7LFIGN3","target":"record","payload":{"canonical_record":{"source":{"id":"2605.16087","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-15T15:47:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ddd5e74aaf1824137518e8e0cb05519e581c345362cac92786b3329948660e82","abstract_canon_sha256":"10d5a9d087627af402f2d8d2ef828392af3433fadfe6d07e3a62b0e8cdbff9ad"},"schema_version":"1.0"},"canonical_sha256":"08ffb55aeb3d3c8e46f1add9f595066eec2f5e4ddfdca94344f41ba6ac350174","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:01:52.099175Z","signature_b64":"dEMgp8xaG8I86eJN5yD59rgIjbGvfkLfeJcVT9Sv/My8IF3CDlSRJcsRscl5pYTr/wyqeKSk+7IdmIMKHMzpBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08ffb55aeb3d3c8e46f1add9f595066eec2f5e4ddfdca94344f41ba6ac350174","last_reissued_at":"2026-05-20T00:01:52.098544Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:01:52.098544Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.16087","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":"2026-05-20T00:01:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0R6zaED5NDhU8QWK0QIYcjLo8N5nkxwLmnf2HV099dGNM8iRT3y3FwaqeHdHpNiaMm6bu3ysx9cNrKL89pFgDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T21:35:28.411742Z"},"content_sha256":"a5fd8f4cbf703c1d313aad620014d0fe32e1cf38d0458229e24b66f532821d7e","schema_version":"1.0","event_id":"sha256:a5fd8f4cbf703c1d313aad620014d0fe32e1cf38d0458229e24b66f532821d7e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:BD73KWXLHU6I4RXRVXM7LFIGN3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Trustworthy and Explainable AI for Perception Models: From Concept to Prototype Vehicle Deployment","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Ayushman Choudhuri, Lutz Eckstein, Manas Mehrotra, Shayan Sharifi, Till Beemelmanns","submitted_at":"2026-05-15T15:47:01Z","abstract_excerpt":"Deep Neural Networks have become the dominant solution for Autonomous Driving perception, but their opacity conflicts with emerging Trustworthy AI guidelines and complicates safety assurance, debugging, and human oversight. While theoretical frameworks for safe and Explainable AI (XAI) exist, concrete implementations of Trustworthy AI for 3D scene understanding remain scarce. We address this gap by proposing a Trustworthy AI perception module that is remarkably robust, integrates faithful explainability, and calibrated uncertainty estimates. Building on a transformer-based detector, we derive "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16087","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/2605.16087/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:41.533018Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T16:41:55.499765Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"3747e7fbb10109272f78940f6e748cf96fc455aa9e41e0d529f430993c4d63fe"},"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":"2026-05-20T00:01:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K9HS2E8dWPUUgQp65LuwtaVj2h9rpDe497ynWt61C3TERxFzT2+Em5r8GAgNwaDwXpUSkLwkYuzFiNzjFS4GCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T21:35:28.412732Z"},"content_sha256":"22b12259896dfdaf9a465a50c2f39355e9efbbec1673c626bf39d03e2041d553","schema_version":"1.0","event_id":"sha256:22b12259896dfdaf9a465a50c2f39355e9efbbec1673c626bf39d03e2041d553"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BD73KWXLHU6I4RXRVXM7LFIGN3/bundle.json","state_url":"https://pith.science/pith/BD73KWXLHU6I4RXRVXM7LFIGN3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BD73KWXLHU6I4RXRVXM7LFIGN3/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":"2026-06-10T21:35:28Z","links":{"resolver":"https://pith.science/pith/BD73KWXLHU6I4RXRVXM7LFIGN3","bundle":"https://pith.science/pith/BD73KWXLHU6I4RXRVXM7LFIGN3/bundle.json","state":"https://pith.science/pith/BD73KWXLHU6I4RXRVXM7LFIGN3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BD73KWXLHU6I4RXRVXM7LFIGN3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BD73KWXLHU6I4RXRVXM7LFIGN3","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":"10d5a9d087627af402f2d8d2ef828392af3433fadfe6d07e3a62b0e8cdbff9ad","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-15T15:47:01Z","title_canon_sha256":"ddd5e74aaf1824137518e8e0cb05519e581c345362cac92786b3329948660e82"},"schema_version":"1.0","source":{"id":"2605.16087","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16087","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16087v1","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16087","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"pith_short_12","alias_value":"BD73KWXLHU6I","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"pith_short_16","alias_value":"BD73KWXLHU6I4RXR","created_at":"2026-05-20T00:01:52Z"},{"alias_kind":"pith_short_8","alias_value":"BD73KWXL","created_at":"2026-05-20T00:01:52Z"}],"graph_snapshots":[{"event_id":"sha256:22b12259896dfdaf9a465a50c2f39355e9efbbec1673c626bf39d03e2041d553","target":"graph","created_at":"2026-05-20T00:01:52Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:41.533018Z","status":"skipped","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T16:41:55.499765Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.16087/integrity.json","findings":[],"snapshot_sha256":"3747e7fbb10109272f78940f6e748cf96fc455aa9e41e0d529f430993c4d63fe","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Neural Networks have become the dominant solution for Autonomous Driving perception, but their opacity conflicts with emerging Trustworthy AI guidelines and complicates safety assurance, debugging, and human oversight. While theoretical frameworks for safe and Explainable AI (XAI) exist, concrete implementations of Trustworthy AI for 3D scene understanding remain scarce. We address this gap by proposing a Trustworthy AI perception module that is remarkably robust, integrates faithful explainability, and calibrated uncertainty estimates. Building on a transformer-based detector, we derive ","authors_text":"Ayushman Choudhuri, Lutz Eckstein, Manas Mehrotra, Shayan Sharifi, Till Beemelmanns","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-15T15:47:01Z","title":"Towards Trustworthy and Explainable AI for Perception Models: From Concept to Prototype Vehicle Deployment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16087","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:a5fd8f4cbf703c1d313aad620014d0fe32e1cf38d0458229e24b66f532821d7e","target":"record","created_at":"2026-05-20T00:01:52Z","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":"10d5a9d087627af402f2d8d2ef828392af3433fadfe6d07e3a62b0e8cdbff9ad","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-15T15:47:01Z","title_canon_sha256":"ddd5e74aaf1824137518e8e0cb05519e581c345362cac92786b3329948660e82"},"schema_version":"1.0","source":{"id":"2605.16087","kind":"arxiv","version":1}},"canonical_sha256":"08ffb55aeb3d3c8e46f1add9f595066eec2f5e4ddfdca94344f41ba6ac350174","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08ffb55aeb3d3c8e46f1add9f595066eec2f5e4ddfdca94344f41ba6ac350174","first_computed_at":"2026-05-20T00:01:52.098544Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:01:52.098544Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dEMgp8xaG8I86eJN5yD59rgIjbGvfkLfeJcVT9Sv/My8IF3CDlSRJcsRscl5pYTr/wyqeKSk+7IdmIMKHMzpBQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:01:52.099175Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.16087","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a5fd8f4cbf703c1d313aad620014d0fe32e1cf38d0458229e24b66f532821d7e","sha256:22b12259896dfdaf9a465a50c2f39355e9efbbec1673c626bf39d03e2041d553"],"state_sha256":"6f73f2d2df0d548b68b0fd0af78c591d376ae6b72db25c054584adb160a47587"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9vK/VD8kAgb/yX390oQ6raaLAfFvN90wgO8tQm/5BmySeezZg2+CWGoStspdUqCOr56kzVYYMsSgnYMyJsO/Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T21:35:28.417464Z","bundle_sha256":"5fd4979959361202bb32fc15c7b69b721b4f2ac234521a6a8b9124d15cba9117"}}