{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:5IYK6CM22D2JMF5CUJSG33DNUI","short_pith_number":"pith:5IYK6CM2","canonical_record":{"source":{"id":"2605.17229","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-17T02:30:02Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"d2b2945dcad223ee7da399980895ca6855bfc9ef607f76ec463268e55b989b74","abstract_canon_sha256":"f6c57ddb1b7017dfb346604966ddb6bdd70331fd30c885bf2f9d07cc417c77eb"},"schema_version":"1.0"},"canonical_sha256":"ea30af099ad0f49617a2a2646dec6da2352ce5d8e74a705ff76b07291c1942ec","source":{"kind":"arxiv","id":"2605.17229","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17229","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17229v1","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17229","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"pith_short_12","alias_value":"5IYK6CM22D2J","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"pith_short_16","alias_value":"5IYK6CM22D2JMF5C","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"pith_short_8","alias_value":"5IYK6CM2","created_at":"2026-05-20T00:03:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:5IYK6CM22D2JMF5CUJSG33DNUI","target":"record","payload":{"canonical_record":{"source":{"id":"2605.17229","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-17T02:30:02Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"d2b2945dcad223ee7da399980895ca6855bfc9ef607f76ec463268e55b989b74","abstract_canon_sha256":"f6c57ddb1b7017dfb346604966ddb6bdd70331fd30c885bf2f9d07cc417c77eb"},"schema_version":"1.0"},"canonical_sha256":"ea30af099ad0f49617a2a2646dec6da2352ce5d8e74a705ff76b07291c1942ec","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:03:46.518568Z","signature_b64":"NBYv7w6xwxsA+a7WJbvaMk5rahpTzr/Uxmv80HUiBiGuTno0PVzWUh0cDgQDXsBFeu6UhITLvW8EGm6EGh7+DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea30af099ad0f49617a2a2646dec6da2352ce5d8e74a705ff76b07291c1942ec","last_reissued_at":"2026-05-20T00:03:46.517708Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:03:46.517708Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.17229","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":"2026-05-20T00:03:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a8vWb0LTJh28UQ98JWkHZtns2VJ8Pnxw9fOaizKXBLHeSgz2CQ+8ZGRWkx1uvaTY0ewUlLN31W49dJKuxzafDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:46:53.086764Z"},"content_sha256":"1f2d449a0d882b6c940851c8bb3afc8393e63f3bb126108ae4e26144b1eef68c","schema_version":"1.0","event_id":"sha256:1f2d449a0d882b6c940851c8bb3afc8393e63f3bb126108ae4e26144b1eef68c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:5IYK6CM22D2JMF5CUJSG33DNUI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Guocong Zhai, Kun Xie, Qingwen Pu, Yuan Zhu","submitted_at":"2026-05-17T02:30:02Z","abstract_excerpt":"Automated driving system deployment requires rigorous validation across safety-critical vehicle-pedestrian interactions, yet real-world datasets rarely capture high-risk scenarios while simulation platforms lack realistic behavior. In response, this study proposes a three-stage framework that combines real-world grounding with adaptive simulation to generate behaviorally realistic safety-critical scenarios at scale. Stage 1 pre-trains multi-agent state-space Transformer-enhanced DDPG (MA-SST-DDPG) agents on real-world safety-critical data to learn human-like interactive evasive behaviors throu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17229","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/2605.17229/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-19T22:01:57.900439Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.803630Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"ab520818fd1391e9b0bdc133f9560bd55cc0a133ca7463450b061d8b208943a6"},"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":"2026-05-20T00:03:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kC2QaAe+Ue2JzsO/OF7KASSJg0hlLjnEiJOhJoxwHskVmw/CyjTys4eDwviA/FO3lZzbKCr15US445NVqeGXCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:46:53.087634Z"},"content_sha256":"0ef97b0bf1bf56211dc170c5491e4adde48aa1f0423eb5cb708d664f55788e8e","schema_version":"1.0","event_id":"sha256:0ef97b0bf1bf56211dc170c5491e4adde48aa1f0423eb5cb708d664f55788e8e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5IYK6CM22D2JMF5CUJSG33DNUI/bundle.json","state_url":"https://pith.science/pith/5IYK6CM22D2JMF5CUJSG33DNUI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5IYK6CM22D2JMF5CUJSG33DNUI/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":"2026-06-01T19:46:53Z","links":{"resolver":"https://pith.science/pith/5IYK6CM22D2JMF5CUJSG33DNUI","bundle":"https://pith.science/pith/5IYK6CM22D2JMF5CUJSG33DNUI/bundle.json","state":"https://pith.science/pith/5IYK6CM22D2JMF5CUJSG33DNUI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5IYK6CM22D2JMF5CUJSG33DNUI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5IYK6CM22D2JMF5CUJSG33DNUI","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":"f6c57ddb1b7017dfb346604966ddb6bdd70331fd30c885bf2f9d07cc417c77eb","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-17T02:30:02Z","title_canon_sha256":"d2b2945dcad223ee7da399980895ca6855bfc9ef607f76ec463268e55b989b74"},"schema_version":"1.0","source":{"id":"2605.17229","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17229","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17229v1","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17229","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"pith_short_12","alias_value":"5IYK6CM22D2J","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"pith_short_16","alias_value":"5IYK6CM22D2JMF5C","created_at":"2026-05-20T00:03:46Z"},{"alias_kind":"pith_short_8","alias_value":"5IYK6CM2","created_at":"2026-05-20T00:03:46Z"}],"graph_snapshots":[{"event_id":"sha256:0ef97b0bf1bf56211dc170c5491e4adde48aa1f0423eb5cb708d664f55788e8e","target":"graph","created_at":"2026-05-20T00:03:46Z","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":"claim_evidence","ran_at":"2026-05-19T22:01:57.900439Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.803630Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.17229/integrity.json","findings":[],"snapshot_sha256":"ab520818fd1391e9b0bdc133f9560bd55cc0a133ca7463450b061d8b208943a6","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automated driving system deployment requires rigorous validation across safety-critical vehicle-pedestrian interactions, yet real-world datasets rarely capture high-risk scenarios while simulation platforms lack realistic behavior. In response, this study proposes a three-stage framework that combines real-world grounding with adaptive simulation to generate behaviorally realistic safety-critical scenarios at scale. Stage 1 pre-trains multi-agent state-space Transformer-enhanced DDPG (MA-SST-DDPG) agents on real-world safety-critical data to learn human-like interactive evasive behaviors throu","authors_text":"Guocong Zhai, Kun Xie, Qingwen Pu, Yuan Zhu","cross_cats":["cs.SY","eess.SY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-17T02:30:02Z","title":"Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17229","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":"sha256:1f2d449a0d882b6c940851c8bb3afc8393e63f3bb126108ae4e26144b1eef68c","target":"record","created_at":"2026-05-20T00:03:46Z","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":"f6c57ddb1b7017dfb346604966ddb6bdd70331fd30c885bf2f9d07cc417c77eb","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-17T02:30:02Z","title_canon_sha256":"d2b2945dcad223ee7da399980895ca6855bfc9ef607f76ec463268e55b989b74"},"schema_version":"1.0","source":{"id":"2605.17229","kind":"arxiv","version":1}},"canonical_sha256":"ea30af099ad0f49617a2a2646dec6da2352ce5d8e74a705ff76b07291c1942ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ea30af099ad0f49617a2a2646dec6da2352ce5d8e74a705ff76b07291c1942ec","first_computed_at":"2026-05-20T00:03:46.517708Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:03:46.517708Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NBYv7w6xwxsA+a7WJbvaMk5rahpTzr/Uxmv80HUiBiGuTno0PVzWUh0cDgQDXsBFeu6UhITLvW8EGm6EGh7+DQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:03:46.518568Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17229","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f2d449a0d882b6c940851c8bb3afc8393e63f3bb126108ae4e26144b1eef68c","sha256:0ef97b0bf1bf56211dc170c5491e4adde48aa1f0423eb5cb708d664f55788e8e"],"state_sha256":"c492a13ed06442795c58514a68d15291f7d90dca7c75e24d475f7dcb3348adae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q5jT/yK9Q1KxjWIIzuFRJcyXxwDZ7E+h/GRTuCatbQNw/rGvj+PKladuXcO8KjJX8oVVzpCs+plhRk1FTl4sBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T19:46:53.089803Z","bundle_sha256":"ea9f19173638a6da3b461efb65253b0eca08514c4e11ee9f72c06c306632d28e"}}