{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:MJ7IRJHTVXALPSBAPBW2HKE5WW","short_pith_number":"pith:MJ7IRJHT","schema_version":"1.0","canonical_sha256":"627e88a4f3adc0b7c820786da3a89db5b19009ae2bed99956683bfe84653cf07","source":{"kind":"arxiv","id":"2411.18013","version":1},"attestation_state":"computed","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"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"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"},"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"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.18013","created_at":"2026-07-05T09:41:10.316874+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.18013v1","created_at":"2026-07-05T09:41:10.316874+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.18013","created_at":"2026-07-05T09:41:10.316874+00:00"},{"alias_kind":"pith_short_12","alias_value":"MJ7IRJHTVXAL","created_at":"2026-07-05T09:41:10.316874+00:00"},{"alias_kind":"pith_short_16","alias_value":"MJ7IRJHTVXALPSBA","created_at":"2026-07-05T09:41:10.316874+00:00"},{"alias_kind":"pith_short_8","alias_value":"MJ7IRJHT","created_at":"2026-07-05T09:41:10.316874+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":6,"internal_anchor_count":2,"sample":[{"citing_arxiv_id":"2607.08359","citing_title":"FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation","ref_index":35,"is_internal_anchor":true},{"citing_arxiv_id":"2604.18483","citing_title":"Steadily moving semi-infinite fracture in plane poroelasticity","ref_index":80,"is_internal_anchor":true},{"citing_arxiv_id":"2606.25509","citing_title":"ASSCG: Just-Right Gating over Chattering for Fast-Slow LLM Planning in Autonomous Driving","ref_index":24,"is_internal_anchor":false},{"citing_arxiv_id":"2606.08684","citing_title":"BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Driving","ref_index":6,"is_internal_anchor":false},{"citing_arxiv_id":"2605.17610","citing_title":"SafeLens: Deliberate and Efficient Video Guardrails with Fast-and-Slow Screening","ref_index":43,"is_internal_anchor":false},{"citing_arxiv_id":"2604.18484","citing_title":"XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments","ref_index":80,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW","json":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW.json","graph_json":"https://pith.science/api/pith-number/MJ7IRJHTVXALPSBAPBW2HKE5WW/graph.json","events_json":"https://pith.science/api/pith-number/MJ7IRJHTVXALPSBAPBW2HKE5WW/events.json","paper":"https://pith.science/paper/MJ7IRJHT"},"agent_actions":{"view_html":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW","download_json":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW.json","view_paper":"https://pith.science/paper/MJ7IRJHT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.18013&json=true","fetch_graph":"https://pith.science/api/pith-number/MJ7IRJHTVXALPSBAPBW2HKE5WW/graph.json","fetch_events":"https://pith.science/api/pith-number/MJ7IRJHTVXALPSBAPBW2HKE5WW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/action/storage_attestation","attest_author":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/action/author_attestation","sign_citation":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/action/citation_signature","submit_replication":"https://pith.science/pith/MJ7IRJHTVXALPSBAPBW2HKE5WW/action/replication_record"}},"created_at":"2026-07-05T09:41:10.316874+00:00","updated_at":"2026-07-05T09:41:10.316874+00:00"}