{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RQUFLKU5XG5ASMCMMTIQOXI4IH","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":"5f71270b026e06b9b4b8939044ff267e00c2aec76b97427254e64ad26260fb3e","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2024-09-16T19:08:50Z","title_canon_sha256":"9c20bdf9bb10e784ca2983f99b8b9ecd3c093ce1ca78e00de13aeed36d957e1d"},"schema_version":"1.0","source":{"id":"2409.10669","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.10669","created_at":"2026-07-05T09:07:54Z"},{"alias_kind":"arxiv_version","alias_value":"2409.10669v1","created_at":"2026-07-05T09:07:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.10669","created_at":"2026-07-05T09:07:54Z"},{"alias_kind":"pith_short_12","alias_value":"RQUFLKU5XG5A","created_at":"2026-07-05T09:07:54Z"},{"alias_kind":"pith_short_16","alias_value":"RQUFLKU5XG5ASMCM","created_at":"2026-07-05T09:07:54Z"},{"alias_kind":"pith_short_8","alias_value":"RQUFLKU5","created_at":"2026-07-05T09:07:54Z"}],"graph_snapshots":[{"event_id":"sha256:b6c3ee3b098dc84f2ddb7a5418fbae7c62ba7c0f7c1c2f032b65b66bb6b58783","target":"graph","created_at":"2026-07-05T09:07:54Z","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/2409.10669/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work introduces a framework to diagnose the strengths and shortcomings of Autonomous Vehicle (AV) collision avoidance technology with synthetic yet realistic potential collision scenarios adapted from real-world, collision-free data. Our framework generates counterfactual collisions with diverse crash properties, e.g., crash angle and velocity, between an adversary and a target vehicle by adding perturbations to the adversary's predicted trajectory from a learned AV behavior model. Our main contribution is to ground these adversarial perturbations in realistic behavior as defined through ","authors_text":"Edward Schmerling, Luigi Di Lillo, Marco Pavone, Matthew Foutter, Robert Dyro, Ruolin Li, Xilin Zhou","cross_cats":["cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2024-09-16T19:08:50Z","title":"Realistic Extreme Behavior Generation for Improved AV Testing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.10669","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:d60f54162f139736841ead2e7fd0b5b03207a8008099d13457c46b6e5359bb7d","target":"record","created_at":"2026-07-05T09:07:54Z","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":"5f71270b026e06b9b4b8939044ff267e00c2aec76b97427254e64ad26260fb3e","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2024-09-16T19:08:50Z","title_canon_sha256":"9c20bdf9bb10e784ca2983f99b8b9ecd3c093ce1ca78e00de13aeed36d957e1d"},"schema_version":"1.0","source":{"id":"2409.10669","kind":"arxiv","version":1}},"canonical_sha256":"8c2855aa9db9ba09304c64d1075d1c41cd3af20d3e40b5d81b9b535196a62c87","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c2855aa9db9ba09304c64d1075d1c41cd3af20d3e40b5d81b9b535196a62c87","first_computed_at":"2026-07-05T09:07:54.466268Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:07:54.466268Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9XYl1sSIljxN32sv4fWvS8b4BdADZmMLnKddxEM0qNLPBH6qODkYffm367DASUkzm+FK5EKTmKl93P5b94CCAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:07:54.466725Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.10669","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d60f54162f139736841ead2e7fd0b5b03207a8008099d13457c46b6e5359bb7d","sha256:b6c3ee3b098dc84f2ddb7a5418fbae7c62ba7c0f7c1c2f032b65b66bb6b58783"],"state_sha256":"27959ccfcfee5592b479fd677c8ddf413663fa431ea9ac67b2a1ec189b74e336"}