{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DRYEVO3WOXGHACGMJAHXSVY5MJ","short_pith_number":"pith:DRYEVO3W","canonical_record":{"source":{"id":"2403.16289","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-24T20:40:51Z","cross_cats_sorted":[],"title_canon_sha256":"aea3ec906c1ea73808577ee2866ba58ecbd2964ee41acca031dbf642a1fbd574","abstract_canon_sha256":"c3d829290207433a8c3dc5181440491b797137adb772591bd36f6509e64d7e09"},"schema_version":"1.0"},"canonical_sha256":"1c704abb7675cc7008cc480f79571d6249ca2621794c739ae95deccef58d5caf","source":{"kind":"arxiv","id":"2403.16289","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.16289","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"arxiv_version","alias_value":"2403.16289v1","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.16289","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"pith_short_12","alias_value":"DRYEVO3WOXGH","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"pith_short_16","alias_value":"DRYEVO3WOXGHACGM","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"pith_short_8","alias_value":"DRYEVO3W","created_at":"2026-07-05T08:00:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DRYEVO3WOXGHACGMJAHXSVY5MJ","target":"record","payload":{"canonical_record":{"source":{"id":"2403.16289","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-24T20:40:51Z","cross_cats_sorted":[],"title_canon_sha256":"aea3ec906c1ea73808577ee2866ba58ecbd2964ee41acca031dbf642a1fbd574","abstract_canon_sha256":"c3d829290207433a8c3dc5181440491b797137adb772591bd36f6509e64d7e09"},"schema_version":"1.0"},"canonical_sha256":"1c704abb7675cc7008cc480f79571d6249ca2621794c739ae95deccef58d5caf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:00:13.495293Z","signature_b64":"0gTeHTg1kWNKNo82E0UzM9jTUMRENQqlKtgfT1SnHHiIJqc1eEOZw5e6mMgrBv8LGC+9BFXA9lqEYt1UBr2qDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c704abb7675cc7008cc480f79571d6249ca2621794c739ae95deccef58d5caf","last_reissued_at":"2026-07-05T08:00:13.494752Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:00:13.494752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.16289","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":"2026-07-05T08:00:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gsL2FKc6awzawMNH6wBRG2E8SfY3PE+nKd+/zcQevVXoSIFZT0OVM+FDGfs8lv/9NX41r/EUEfAHwqZy2o6rBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T09:14:01.528732Z"},"content_sha256":"6f3c5e2c88a101d6e02f01940fa49debad1e688610ef17e028be3470e5c1864d","schema_version":"1.0","event_id":"sha256:6f3c5e2c88a101d6e02f01940fa49debad1e688610ef17e028be3470e5c1864d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DRYEVO3WOXGHACGMJAHXSVY5MJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Engineering Safety Requirements for Autonomous Driving with Large Language Models","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ali Nouri, Beatriz Cabrero-Daniel, Christian Berger, Fredrik T\\\"orner, H\\.akan Sivencrona","submitted_at":"2024-03-24T20:40:51Z","abstract_excerpt":"Changes and updates in the requirement artifacts, which can be frequent in the automotive domain, are a challenge for SafetyOps. Large Language Models (LLMs), with their impressive natural language understanding and generating capabilities, can play a key role in automatically refining and decomposing requirements after each update. In this study, we propose a prototype of a pipeline of prompts and LLMs that receives an item definition and outputs solutions in the form of safety requirements. This pipeline also performs a review of the requirement dataset and identifies redundant or contradict"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.16289","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/2403.16289/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:00:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e0A9Up72hljW7mVwHEL/yB4Jr0+kGYM9UJ2w6Ir3CuKf+Qevo3Z8tjybnlda6igKOGP93elh53Jr3FqSnxZQCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T09:14:01.529328Z"},"content_sha256":"1340e161e058b3a3084cb982991dffc96f79d08aa448a60b36f4960cfbca6d5f","schema_version":"1.0","event_id":"sha256:1340e161e058b3a3084cb982991dffc96f79d08aa448a60b36f4960cfbca6d5f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ/bundle.json","state_url":"https://pith.science/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ/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":"2026-08-21T09:14:01Z","links":{"resolver":"https://pith.science/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ","bundle":"https://pith.science/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ/bundle.json","state":"https://pith.science/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DRYEVO3WOXGHACGMJAHXSVY5MJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DRYEVO3WOXGHACGMJAHXSVY5MJ","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":"c3d829290207433a8c3dc5181440491b797137adb772591bd36f6509e64d7e09","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-24T20:40:51Z","title_canon_sha256":"aea3ec906c1ea73808577ee2866ba58ecbd2964ee41acca031dbf642a1fbd574"},"schema_version":"1.0","source":{"id":"2403.16289","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.16289","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"arxiv_version","alias_value":"2403.16289v1","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.16289","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"pith_short_12","alias_value":"DRYEVO3WOXGH","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"pith_short_16","alias_value":"DRYEVO3WOXGHACGM","created_at":"2026-07-05T08:00:13Z"},{"alias_kind":"pith_short_8","alias_value":"DRYEVO3W","created_at":"2026-07-05T08:00:13Z"}],"graph_snapshots":[{"event_id":"sha256:1340e161e058b3a3084cb982991dffc96f79d08aa448a60b36f4960cfbca6d5f","target":"graph","created_at":"2026-07-05T08:00:13Z","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/2403.16289/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Changes and updates in the requirement artifacts, which can be frequent in the automotive domain, are a challenge for SafetyOps. Large Language Models (LLMs), with their impressive natural language understanding and generating capabilities, can play a key role in automatically refining and decomposing requirements after each update. In this study, we propose a prototype of a pipeline of prompts and LLMs that receives an item definition and outputs solutions in the form of safety requirements. This pipeline also performs a review of the requirement dataset and identifies redundant or contradict","authors_text":"Ali Nouri, Beatriz Cabrero-Daniel, Christian Berger, Fredrik T\\\"orner, H\\.akan Sivencrona","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-24T20:40:51Z","title":"Engineering Safety Requirements for Autonomous Driving with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.16289","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":"sha256:6f3c5e2c88a101d6e02f01940fa49debad1e688610ef17e028be3470e5c1864d","target":"record","created_at":"2026-07-05T08:00:13Z","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":"c3d829290207433a8c3dc5181440491b797137adb772591bd36f6509e64d7e09","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-24T20:40:51Z","title_canon_sha256":"aea3ec906c1ea73808577ee2866ba58ecbd2964ee41acca031dbf642a1fbd574"},"schema_version":"1.0","source":{"id":"2403.16289","kind":"arxiv","version":1}},"canonical_sha256":"1c704abb7675cc7008cc480f79571d6249ca2621794c739ae95deccef58d5caf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c704abb7675cc7008cc480f79571d6249ca2621794c739ae95deccef58d5caf","first_computed_at":"2026-07-05T08:00:13.494752Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:00:13.494752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0gTeHTg1kWNKNo82E0UzM9jTUMRENQqlKtgfT1SnHHiIJqc1eEOZw5e6mMgrBv8LGC+9BFXA9lqEYt1UBr2qDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:00:13.495293Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.16289","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6f3c5e2c88a101d6e02f01940fa49debad1e688610ef17e028be3470e5c1864d","sha256:1340e161e058b3a3084cb982991dffc96f79d08aa448a60b36f4960cfbca6d5f"],"state_sha256":"f7faaaf3c790d24e84229d81bd15a46fe3bc4fb64aa020b9235627214c68932f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+rpQuFni+TXRBFemNRWC910WLCsYrVi1RhxsZKvmLxziZWKX2xhBzIPos2pIJzA9XYU+hym7N9Y/WdTtCBTBDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T09:14:01.539066Z","bundle_sha256":"9260b27bc223443129d732aef3ecbbdac47fbc05b1785fe565031a5553b9cf19"}}