Paper Citation Record · LEDGER

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM)

As of 14 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2501.10839.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.10839 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:59:07.484901Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact2
verified fuzzy22
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 358aa3b3-5073-411a-8309-0ab2def4c0c3 · outbound

This paper cites Waymo's Safety Methodologies and Safety Readiness Determinations.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Waymo's Safety Methodologies and Safety Readiness Determinations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T18:59:07.388296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d776604-b8d1-454b-a95c-d26efcc8310f · outbound

This paper cites Framework for a conflict typology including contributing factors for use in ads safety evaluation.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Framework for a conflict typology including contributing factors for use in ads safety evaluation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.881267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7f194cef-2acc-4b84-b933-df913a7e56b0 · outbound

This paper cites Hierarchical model-based imitation learning for planning in autonomous driving.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Hierarchical model-based imitation learning for planning in autonomous driving

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.869580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 61bd2e05-9d49-477c-aaca-66d537d7681f · outbound

This paper cites MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T18:59:07.400639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f894d5a-111d-4f6e-a815-1fe806f892c3 · outbound

This paper cites Probabilistic prediction of vehicle semantic intention and motion.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Probabilistic prediction of vehicle semantic intention and motion

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.857479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dffecb16-9862-4fd6-832f-c5c3bcb05ed1 · outbound

This paper cites Embedding synthetic off-policy experience for autonomous driving via zero-shot curricula.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Embedding synthetic off-policy experience for autonomous driving via zero-shot curricula

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.845264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d2c825a5-8a70-43c2-ab83-5deb3bd5b66d · outbound

This paper cites Systems engineering for its handbook - section 3 what is systems engineering?, 2023.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Systems engineering for its handbook - section 3 what is systems engineering?, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.835674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b8a8aebc-440c-4c38-a414-9b1ada16dac1 · outbound

This paper cites Safe by design autonomous driving systems.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Safe by design autonomous driving systems

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T18:59:07.416562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d25df1-0d97-44a9-b2cf-ef94717404fe · outbound

This paper cites Vehicle dynamics and suspension design using systems engineering.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Vehicle dynamics and suspension design using systems engineering

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.826158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7d524ca1-ce7a-47bc-80b4-7b68499ee9d2 · outbound

This paper cites A survey of algorithms for black-box safety validation of cyber-physical systems.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) A survey of algorithms for black-box safety validation of cyber-physical systems

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.816576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bc7a827e-3a38-4d50-83fb-fbc33d8f5391 · outbound

This paper cites Trustworthy autonomous system development.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Trustworthy autonomous system development

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.805992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a3a8d42a-df91-4e1e-8550-8ad3084f49ac · outbound

This paper cites Driving with llms: Fusing object-level vector modality for explainable autonomous driving.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Driving with llms: Fusing object-level vector modality for explainable autonomous driving

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T18:59:07.430127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eb0f94f-3d4b-45df-a28b-df2709474e45 · outbound

This paper cites Advancing requirements engineering through generative ai: Assessing the role of llms.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Advancing requirements engineering through generative ai: Assessing the role of llms

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T18:59:07.433870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d3188ee-47ee-4230-b9b3-e99ca8033628 · outbound

This paper cites Requirements engineering and large language models: Insights from a panel.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Requirements engineering and large language models: Insights from a panel

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.783188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2b720c5a-8f44-4281-8211-40b3d31aa25c · outbound

This paper cites Normative requirements operational- ization with large language models.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Normative requirements operational- ization with large language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.773442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4f6f40f4-9f56-4179-8a61-bd64a3adb4c7 · outbound

This paper cites Lessons from the Use of Natural Language Inference (NLI) in Requirements Engineering Tasks.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Lessons from the Use of Natural Language Inference (NLI) in Requirements Engineering Tasks

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-10T18:59:07.538458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7cf68b8f-b162-4c12-a80a-9e656a49aa29 · outbound

This paper cites Sae levels of driving automation ™ refined for clarity and international audience.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Sae levels of driving automation ™ refined for clarity and international audience

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.763514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 747a0010-305d-45e8-ad6b-347cf95fb55a · outbound

This paper cites Motion planning constraints for autonomous vehicles, January 25 2024.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Motion planning constraints for autonomous vehicles, January 25 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.752829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4c28f92b-1193-4e61-818b-ba7a7efe0986 · outbound

This paper cites Autonomous systems–an architectural characterization.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Autonomous systems–an architectural characterization

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.741727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d7ba394a-3fa2-4ad3-b4d6-454e6c7a1033 · outbound

This paper cites A review of motion planning techniques for automated vehicles.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) A review of motion planning techniques for automated vehicles

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.729740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d2be3e87-bd18-44b6-9e28-7dcf03584429 · outbound

This paper cites Active suspension system with energy storage device, October 27 2020.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Active suspension system with energy storage device, October 27 2020

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.717703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2553da6a-3e64-4d0c-b699-75c2020b974e · outbound

This paper cites Steer-by-wire system with multiple steering actuators, September 29 2020.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Steer-by-wire system with multiple steering actuators, September 29 2020

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.705944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2e07397b-842f-4583-80de-076b9c3e3a5b · outbound

This paper cites Interactive Joint Planning for Autonomous Vehicles.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Interactive Joint Planning for Autonomous Vehicles

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-10T18:59:07.521803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2d9b6a09-7168-471a-8745-59487da9b24c · outbound

This paper cites Council post: Safety of the intended functionality (sotif) for autonomous driv- ing.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Council post: Safety of the intended functionality (sotif) for autonomous driv- ing

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.693590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f7d47b49-da3f-4a6c-8406-2e3b3aadf9ef · outbound

This paper cites Iso 26262-1:2018, road vehicles — functional safety, part 1: V ocabulary.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Iso 26262-1:2018, road vehicles — functional safety, part 1: V ocabulary

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.681195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d52b8464-9abc-474b-ac07-e3856318fdb4 · outbound

This paper cites A survey on the explainability of supervised machine learning.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) A survey on the explainability of supervised machine learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.669819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ced1d462-b3ad-4d5d-884f-36080c7cdf27 · outbound

This paper cites Driving simulator parameteriza- tion using double-lane change steering metrics as recorded on five modern cars.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Driving simulator parameteriza- tion using double-lane change steering metrics as recorded on five modern cars

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.659357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5de9de3d-25e8-46c6-84a7-3855ca29f63e · outbound

This paper cites Vehicle dynamics and control.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Vehicle dynamics and control

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.648290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f062059e-6bb8-4c1b-9c20-43617d1bc54b · outbound

This paper cites Dynamic programming and optimal control: Volume I, volume 4.

Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM) Dynamic programming and optimal control: Volume I, volume 4

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:59:07.637106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.