{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MJ7IRJHTVXALPSBAPBW2HKE5WW","short_pith_number":"pith:MJ7IRJHT","canonical_record":{"source":{"id":"2411.18013","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-27T03:14:16Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"4503a5e21d4a013b340ed7b626af2e175a11ee8c142c11e8bff126cb1e71e229","abstract_canon_sha256":"231818b02a76440a10e7f3ce9893acc2978344b8366e5bacde98e669a6b87897"},"schema_version":"1.0"},"canonical_sha256":"627e88a4f3adc0b7c820786da3a89db5b19009ae2bed99956683bfe84653cf07","source":{"kind":"arxiv","id":"2411.18013","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.18013","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"arxiv_version","alias_value":"2411.18013v1","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.18013","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"pith_short_12","alias_value":"MJ7IRJHTVXAL","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"pith_short_16","alias_value":"MJ7IRJHTVXALPSBA","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"pith_short_8","alias_value":"MJ7IRJHT","created_at":"2026-07-05T09:41:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MJ7IRJHTVXALPSBAPBW2HKE5WW","target":"record","payload":{"canonical_record":{"source":{"id":"2411.18013","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-27T03:14:16Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"4503a5e21d4a013b340ed7b626af2e175a11ee8c142c11e8bff126cb1e71e229","abstract_canon_sha256":"231818b02a76440a10e7f3ce9893acc2978344b8366e5bacde98e669a6b87897"},"schema_version":"1.0"},"canonical_sha256":"627e88a4f3adc0b7c820786da3a89db5b19009ae2bed99956683bfe84653cf07","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:41:10.317299Z","signature_b64":"9fYwO5nOwimB70WXdbQ6KuxOJN34Ac5rMmqBDcofSqWa9Rb3OZIxGHBGJrCViy2BfLk1UJvUMr1JvC4oM+33Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"627e88a4f3adc0b7c820786da3a89db5b19009ae2bed99956683bfe84653cf07","last_reissued_at":"2026-07-05T09:41:10.316816Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:41:10.316816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.18013","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":"2026-07-05T09:41:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tv+DrZB1tqJI9iajN62iWMt4mTwyu5hm75m9uXsDFJdo+Y2cmHoKuS22PtzYPzaVffndf/l/nECGyY45T7vWDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:49:19.623751Z"},"content_sha256":"b2d68aa653bf0ee5e3a81e25124288e23a967aa8df10e5c2cb7a8e81b629d433","schema_version":"1.0","event_id":"sha256:b2d68aa653bf0ee5e3a81e25124288e23a967aa8df10e5c2cb7a8e81b629d433"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MJ7IRJHTVXALPSBAPBW2HKE5WW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Diange Yang, Jianhui Wang, Jiayin Li, Kangan Qian, Kun Jiang, Takafumi Matsumaru, Tianyu Shi, Tianze Zhu, Xiao He, Xinyu Jiao, Yangfan He, Yining Shi, Zheng Fu, Zhikun Ma, Ziang Luo, Ziyu Chen","submitted_at":"2024-11-27T03:14:16Z","abstract_excerpt":"Ensuring safe, comfortable, and efficient navigation is a critical goal for autonomous driving systems. While end-to-end models trained on large-scale datasets excel in common driving scenarios, they often struggle with rare, long-tail events. Recent progress in large language models (LLMs) has introduced enhanced reasoning capabilities, but their computational demands pose challenges for real-time decision-making and precise planning. This paper presents FASIONAD, a novel dual-system framework inspired by the cognitive model \"Thinking, Fast and Slow.\" The fast system handles routine navigatio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.18013","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/2411.18013/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":"2026-07-05T09:41:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NWnEPHlssqT6AiVJEbor8w5Ol0U6B4TJ12N1Zk0QttrkIEm2oSfzMchucOVDzC8dTSnf5Ci0dtIP36eIjT76Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:49:19.624561Z"},"content_sha256":"0c0d2dbe0f08543c296c9f5fb7698fcadeb2ae6f963092fe58fef7f703398d9a","schema_version":"1.0","event_id":"sha256:0c0d2dbe0f08543c296c9f5fb7698fcadeb2ae6f963092fe58fef7f703398d9a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/bundle.json","state_url":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/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":"2026-08-05T05:49:19Z","links":{"resolver":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW","bundle":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/bundle.json","state":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MJ7IRJHTVXALPSBAPBW2HKE5WW","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":"231818b02a76440a10e7f3ce9893acc2978344b8366e5bacde98e669a6b87897","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-27T03:14:16Z","title_canon_sha256":"4503a5e21d4a013b340ed7b626af2e175a11ee8c142c11e8bff126cb1e71e229"},"schema_version":"1.0","source":{"id":"2411.18013","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.18013","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"arxiv_version","alias_value":"2411.18013v1","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.18013","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"pith_short_12","alias_value":"MJ7IRJHTVXAL","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"pith_short_16","alias_value":"MJ7IRJHTVXALPSBA","created_at":"2026-07-05T09:41:10Z"},{"alias_kind":"pith_short_8","alias_value":"MJ7IRJHT","created_at":"2026-07-05T09:41:10Z"}],"graph_snapshots":[{"event_id":"sha256:0c0d2dbe0f08543c296c9f5fb7698fcadeb2ae6f963092fe58fef7f703398d9a","target":"graph","created_at":"2026-07-05T09:41:10Z","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/2411.18013/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Ensuring safe, comfortable, and efficient navigation is a critical goal for autonomous driving systems. While end-to-end models trained on large-scale datasets excel in common driving scenarios, they often struggle with rare, long-tail events. Recent progress in large language models (LLMs) has introduced enhanced reasoning capabilities, but their computational demands pose challenges for real-time decision-making and precise planning. This paper presents FASIONAD, a novel dual-system framework inspired by the cognitive model \"Thinking, Fast and Slow.\" The fast system handles routine navigatio","authors_text":"Diange Yang, Jianhui Wang, Jiayin Li, Kangan Qian, Kun Jiang, Takafumi Matsumaru, Tianyu Shi, Tianze Zhu, Xiao He, Xinyu Jiao, Yangfan He, Yining Shi, Zheng Fu, Zhikun Ma, Ziang Luo, Ziyu Chen","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-27T03:14:16Z","title":"FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.18013","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:b2d68aa653bf0ee5e3a81e25124288e23a967aa8df10e5c2cb7a8e81b629d433","target":"record","created_at":"2026-07-05T09:41:10Z","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":"231818b02a76440a10e7f3ce9893acc2978344b8366e5bacde98e669a6b87897","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-27T03:14:16Z","title_canon_sha256":"4503a5e21d4a013b340ed7b626af2e175a11ee8c142c11e8bff126cb1e71e229"},"schema_version":"1.0","source":{"id":"2411.18013","kind":"arxiv","version":1}},"canonical_sha256":"627e88a4f3adc0b7c820786da3a89db5b19009ae2bed99956683bfe84653cf07","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"627e88a4f3adc0b7c820786da3a89db5b19009ae2bed99956683bfe84653cf07","first_computed_at":"2026-07-05T09:41:10.316816Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:41:10.316816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9fYwO5nOwimB70WXdbQ6KuxOJN34Ac5rMmqBDcofSqWa9Rb3OZIxGHBGJrCViy2BfLk1UJvUMr1JvC4oM+33Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T09:41:10.317299Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.18013","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b2d68aa653bf0ee5e3a81e25124288e23a967aa8df10e5c2cb7a8e81b629d433","sha256:0c0d2dbe0f08543c296c9f5fb7698fcadeb2ae6f963092fe58fef7f703398d9a"],"state_sha256":"d66af6d67baf7b658d8e5cff388b573efda0cc961f1c72f191a66b434c121ecb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/8mPfHdyZIbX1Da76SyB7nmYHAJvquGnfK7Hm2U+1f+E0PYNs8/835YJPF1lvu1JBxFEXhpC/e5cmkmmyVoGAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T05:49:19.630294Z","bundle_sha256":"7f76e6640eb57478fe29ddb8ae38da4c402b8ab6e7318e826fe62fe21106b968"}}