Paper Citation Record · LEDGER

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving

As of 23 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2505.05223.

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

pith.paper-citation-record.v1
2505.05223 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:16:02.508018Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T07:56:55.207988Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

verified exact0
verified fuzzy36
unresolved6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad383949-887f-4019-bb93-1a9636220cbd · outbound

This paper cites EMMA: End-to-End Multimodal Model for Autonomous Driving.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving EMMA: End-to-End Multimodal Model for Autonomous Driving

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:16:02.338693Z

Source-reported events for the cited work

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Observation 7cb0c473-c98e-4ce3-a4f2-9c7e6e023075 · outbound

This paper cites Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T23:16:02.343595Z

Source-reported events for the cited work

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Observation c000b252-6596-455f-b3fb-9ed1e5608049 · outbound

This paper cites Exploration of the acceptability of different behaviors of an autonomous vehicle in so- called conflict situations,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Exploration of the acceptability of different behaviors of an autonomous vehicle in so- called conflict situations,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:03.045317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9b8308ee-e764-448e-94a9-b2a5afaaa5ac · outbound

This paper cites Toward adaptive driving styles for automated driving with users’ trust and preferences,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Toward adaptive driving styles for automated driving with users’ trust and preferences,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:03.032982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1f821b89-b78b-4131-8082-1a0987c9c465 · outbound

This paper cites Dynamic preferences in multi-criteria reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Dynamic preferences in multi-criteria reinforcement learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:03.020086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad0da834-c7b7-4646-aa04-8679a1a27232 · outbound

This paper cites User-driven adaptation: Tailoring autonomous driving systems with dynamic preferences,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving User-driven adaptation: Tailoring autonomous driving systems with dynamic preferences,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:03.007284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 74ca8899-4174-4077-94ca-9f81b41b4ad4 · outbound

This paper cites Lexicographic actor-critic deep reinforcement learning for urban autonomous driving,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Lexicographic actor-critic deep reinforcement learning for urban autonomous driving,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.993583Z

Source-reported events for the cited work

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Observation 561aff21-84e3-4f70-b97e-cfcc37937302 · outbound

This paper cites Urban driving with multi-objective deep reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Urban driving with multi-objective deep reinforcement learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.980632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9057dfde-ce7d-42ae-99ec-e63efff497c7 · outbound

This paper cites Multi-objective optimization for autonomous driving strategy based on deep q network,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Multi-objective optimization for autonomous driving strategy based on deep q network,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.968134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7ba0fb0b-5426-400c-98aa-63f308bbf733 · outbound

This paper cites Porf-ddpg: Learning per- sonalized autonomous driving behavior with progressively optimized reward function,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Porf-ddpg: Learning per- sonalized autonomous driving behavior with progressively optimized reward function,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.955898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e8863148-8459-43b0-8895-bf55974af567 · outbound

This paper cites Toward personalized decision making for au- tonomous vehicles: A constrained multi-objective reinforcement learn- ing technique,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Toward personalized decision making for au- tonomous vehicles: A constrained multi-objective reinforcement learn- ing technique,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.941621Z

Source-reported events for the cited work

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Observation 359bb56b-463c-4afd-b6d9-14ac331dc0f3 · outbound

This paper cites Navigation in urban environments amongst pedestrians using multi-objective deep reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Navigation in urban environments amongst pedestrians using multi-objective deep reinforcement learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.928714Z

Source-reported events for the cited work

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Observation 4ffd992c-fd44-4375-93c1-19262e8ad85b · outbound

This paper cites Learning driving styles for autonomous vehicles from demonstration,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Learning driving styles for autonomous vehicles from demonstration,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.916769Z

Source-reported events for the cited work

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Observation c53b48f1-6e2c-4df3-9957-af718f030752 · outbound

This paper cites Driving behavior modeling using naturalistic human driving data with inverse reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Driving behavior modeling using naturalistic human driving data with inverse reinforcement learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.904524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1423acff-d206-4a2d-804c-0c761061c7f3 · outbound

This paper cites Driving with style: Inverse reinforcement learning in general-purpose planning for automated driving,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Driving with style: Inverse reinforcement learning in general-purpose planning for automated driving,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.891938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 077aad96-d089-4b42-aa63-6a5bcef9b9b0 · outbound

This paper cites Driving style alignment for llm-powered driver agent,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Driving style alignment for llm-powered driver agent,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.878217Z

Source-reported events for the cited work

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Observation e58df251-3ad6-4a32-9413-beb472a2ee20 · outbound

This paper cites From Words to Wheels: Automated Style-Customized Policy Generation for Autonomous Driving.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving From Words to Wheels: Automated Style-Customized Policy Generation for Autonomous Driving

Reference 17

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Source-reported events for the cited work

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Observation 2cd0e7ed-9cd2-49bd-83f5-33ce5f9114ce · outbound

This paper cites On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation

Reference 18

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Source-reported events for the cited work

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Observation 4a412504-22b3-4a57-939a-8de803e1b85a · outbound

This paper cites A review of personalization in driving behavior: Dataset, modeling, and validation,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving A review of personalization in driving behavior: Dataset, modeling, and validation,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T23:16:02.417498Z

Source-reported events for the cited work

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Observation 35a5f31f-0610-44e8-bf7e-30c1c02e7ea3 · outbound

This paper cites Self-driving like a human driver instead of a robocar: Personalized comfortable driving experience for autonomous vehicles,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Self-driving like a human driver instead of a robocar: Personalized comfortable driving experience for autonomous vehicles,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.856960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 31e00388-de41-4c44-bf24-50ce56bda75d · outbound

This paper cites Toward safe and personal- ized autonomous driving: Decision-making and motion control with dpf and cdt techniques,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Toward safe and personal- ized autonomous driving: Decision-making and motion control with dpf and cdt techniques,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.843565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fc1b08bc-aacd-4417-aec8-26782f9708dc · outbound

This paper cites Personalized driving behavior oriented autonomous vehicle control for typical traffic situations,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Personalized driving behavior oriented autonomous vehicle control for typical traffic situations,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.830825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3ac28ce6-5244-4e55-b70e-9bd8db502ee2 · outbound

This paper cites Recent advancements in end-to-end au- tonomous driving using deep learning: A survey,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Recent advancements in end-to-end au- tonomous driving using deep learning: A survey,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.818302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e0f0e82a-4893-47a1-94cc-6b1c92ea3347 · outbound

This paper cites Personalized car following for autonomous driving with in- verse reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Personalized car following for autonomous driving with in- verse reinforcement learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.805244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 042e9b7b-42dc-4411-af6e-6f70aeb325a1 · outbound

This paper cites Text-to-drive: Diverse driving behavior synthesis via large language models,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Text-to-drive: Diverse driving behavior synthesis via large language models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.792782Z

Source-reported events for the cited work

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Observation 66955f68-3c95-4bb5-8944-f43ad62f7f94 · outbound

This paper cites Multi-objective end-to-end self- driving based on pareto-optimal actor-critic approach,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Multi-objective end-to-end self- driving based on pareto-optimal actor-critic approach,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.780319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 957ab936-fa42-47e1-bae2-9839c6383484 · outbound

This paper cites PD-MORL: Preference-driven multi-objective reinforcement learning algorithm,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving PD-MORL: Preference-driven multi-objective reinforcement learning algorithm,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.768130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 43a560af-2bcf-4774-a351-0af47448711e · outbound

This paper cites Demonstration- enhanced adaptable multi-objective robot navigation,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Demonstration- enhanced adaptable multi-objective robot navigation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.756710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e21630cf-681c-41c4-8282-39f7c81b8946 · outbound

This paper cites CARLA: An open urban driving simulator,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving CARLA: An open urban driving simulator,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.744829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 016b1561-a8e5-4fd4-b5c6-f4903730e1fc · outbound

This paper cites A practical guide to multi-objective reinforcement learning and plan- ning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving A practical guide to multi-objective reinforcement learning and plan- ning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.732009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5d38c2ef-ec9e-46cd-b666-fb484394f327 · outbound

This paper cites Prediction- guided multi-objective reinforcement learning for continuous robot control,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Prediction- guided multi-objective reinforcement learning for continuous robot control,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.719502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3ad0a038-4514-4861-8603-5d8b84939a1f · outbound

This paper cites End-to- end reinforcement learning for autonomous longitudinal control using advantage actor critic with temporal context,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving End-to- end reinforcement learning for autonomous longitudinal control using advantage actor critic with temporal context,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.707534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 094a07a4-a3df-4b96-a1c8-4b72f70692cd · outbound

This paper cites PASRL: Stabilising reinforcement learning with past action-state representation learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving PASRL: Stabilising reinforcement learning with past action-state representation learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.695562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c8c4686a-a6ca-40b7-a822-04e2cf62706a · outbound

This paper cites Transfuser: Imitation with transformer-based sensor fusion for au- tonomous driving,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Transfuser: Imitation with transformer-based sensor fusion for au- tonomous driving,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.683437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5318ac18-48f4-422b-aea7-b8a48da84e23 · outbound

This paper cites Deep residual learning for image recognition,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Deep residual learning for image recognition,

Reference 35

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Source-reported events for the cited work

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Observation 587274d3-436a-407e-814d-fa257416c99b · outbound

This paper cites Model-free deep reinforcement learning for urban autonomous driving,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Model-free deep reinforcement learning for urban autonomous driving,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.664667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b67b49f6-58fd-4b0e-adea-6c47df2af612 · outbound

This paper cites End-to-end model-free reinforcement learning for urban driving using implicit affordances,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving End-to-end model-free reinforcement learning for urban driving using implicit affordances,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.652997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 80df87dd-b42e-441c-88ee-c40488bd2841 · outbound

This paper cites Prioritized experience-based reinforcement learning with human guidance for autonomous driving,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Prioritized experience-based reinforcement learning with human guidance for autonomous driving,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.640310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e99656ec-f3fe-4a2c-b7f7-5d5d62bcf63c · outbound

This paper cites Carla leaderboard,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Carla leaderboard,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.628267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 61b8e8d3-fe9b-4c68-a58f-1b1fa2ed24f0 · outbound

This paper cites Privileged sensing scaffolds reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Privileged sensing scaffolds reinforcement learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.615953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b79813f8-753d-4a16-858a-d011556ba540 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Human-level control through deep reinforcement learning,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.603584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 33ec2fdd-b318-488b-b744-62bb9ab973b4 · outbound

This paper cites Searching for MobileNetV3,.

Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving Searching for MobileNetV3,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:16:02.589447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 1900112c-9271-406c-be81-4b597eb4bb36 · inbound

Multi-Objective Reinforcement Learning for Tactical Decision Making for Trucks in Highway Traffic cites this paper.

Multi-Objective Reinforcement Learning for Tactical Decision Making for Trucks in Highway Traffic Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-03T07:56:55.207988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.