Paper Citation Record · LEDGER

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies

As of 16 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2506.18304.

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

pith.paper-citation-record.v1
2506.18304 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

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measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:43:05.773872Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

58 of 58 outbound references displayed

verified exact2
verified fuzzy14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ef42dad-52b3-4cf5-8b4a-74e72f59770b · outbound

This paper cites To the best of our knowledge, we are the first to integrate expert knowledge into adversarial attack training for DRL-based autonomous driving policies.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies To the best of our knowledge, we are the first to integrate expert knowledge into adversarial attack training for DRL-based autonomous driving policies

Reference 1

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Observation 85cb1c72-e10c-4994-a8f7-a2acb83d43c8 · outbound

This paper cites This design enables the expert to better capture diverse attack policies across various scenarios.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies This design enables the expert to better capture diverse attack policies across various scenarios

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:56:36.670496Z

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Observation 0f2fa9d1-8971-406f-b59c-761310dafc93 · outbound

This paper cites an unresolved cited work.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Unresolved cited work

Reference 3

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Observation 9fe5ed70-ca57-49b3-b167-f896021149e1 · outbound

This paper cites A survey of decision-making and planning methods for self- driving vehicles,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies A survey of decision-making and planning methods for self- driving vehicles,

Reference 4

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Observation 00030726-57f7-4015-bd39-fc5e9457694a · outbound

This paper cites However, effective attack opportunities are temporally sparse and context-dependent.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies However, effective attack opportunities are temporally sparse and context-dependent

Reference 5

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Source-reported events for the cited work

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Observation aef0fcb7-dfe1-468d-9432-a8bd2b6d4d80 · outbound

This paper cites However, such trial -and- error exploration is highly inefficient, especially under strict attack budgets and sparse rewards.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies However, such trial -and- error exploration is highly inefficient, especially under strict attack budgets and sparse rewards

Reference 6

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Observation 4f7670d0-1e3a-434b-9939-5edc417d6e93 · outbound

This paper cites This su boptimality can mislead adversary training and limit its overall effectiveness if left unaddressed.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies This su boptimality can mislead adversary training and limit its overall effectiveness if left unaddressed

Reference 7

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Observation f57b6625-88a0-4445-b8bb-1a900366bfa2 · outbound

This paper cites an unresolved cited work.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Unresolved cited work

Reference 8

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Observation 26aa3e26-97b8-44bf-affe-a31e4181d839 · outbound

This paper cites A Survey on Recent Advancements in Autonomous Driving Using Deep Reinforcement Learning: Applications, Challenges, and Solutions,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies A Survey on Recent Advancements in Autonomous Driving Using Deep Reinforcement Learning: Applications, Challenges, and Solutions,

Reference 9

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Observation 92e6c27b-75a5-4c5e-95dd-38115bfaf42e · outbound

This paper cites Reinforcement Learning -Based Multi-Lane Cooperative Control for On -Ramp Merging in Mixed - Autonomy Traffic,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Reinforcement Learning -Based Multi-Lane Cooperative Control for On -Ramp Merging in Mixed - Autonomy Traffic,

Reference 10

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Observation 16d21b7b-e2f2-46f7-9314-32f1a287bb55 · outbound

This paper cites Research on Autonomous Driving Deci sion-making Strategies based Deep Reinforcement Learning,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Research on Autonomous Driving Deci sion-making Strategies based Deep Reinforcement Learning,

Reference 11

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Observation 6fce662c-136a-4718-8ad9-8fc65bccb48d · outbound

This paper cites Seeing is not Believing: Robust Reinforcement Learning ag ainst Spurious Correlation,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Seeing is not Believing: Robust Reinforcement Learning ag ainst Spurious Correlation,

Reference 13

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Observation ded85b9e-4810-43f9-b791-56ef3fa5bddb · outbound

This paper cites Adversarial Machine Learning Attacks and Defences in Multi- Agent Reinforcement Learning,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Adversarial Machine Learning Attacks and Defences in Multi- Agent Reinforcement Learning,

Reference 14

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Observation e68f759b-4fbe-410f-b2c7-e35e55a79df3 · outbound

This paper cites Adversarial Attacks and Countermeasures on Image Classification-based Deep Learning Models in Autonomous Driving Systems: A Systematic Review,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Adversarial Attacks and Countermeasures on Image Classification-based Deep Learning Models in Autonomous Driving Systems: A Systematic Review,

Reference 15

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Observation 96039cf8-a467-4ce3-aa93-ced6ef78f96d · outbound

This paper cites Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns,

Reference 16

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Observation 147cd533-1506-4083-9fc9-95252425be7e · outbound

This paper cites Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi -agent Autonomous Driving Policies,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi -agent Autonomous Driving Policies,

Reference 17

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Observation 8277e85e-a7e7-4ec5-93c6-a2ccfc2cd8cb · outbound

This paper cites Deep learning adversarial attacks and defenses in autonomous vehicles: a systematic literature review from a safety perspective,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Deep learning adversarial attacks and defenses in autonomous vehicles: a systematic literature review from a safety perspective,

Reference 18

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Observation 9fd17436-f455-4271-99db-25a41934d6dd · outbound

This paper cites Toward Trustworthy Decision -Making for Autonomous Vehicles: A Robust Reinforcement Learning Approach with Safety Guarantees,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Toward Trustworthy Decision -Making for Autonomous Vehicles: A Robust Reinforcement Learning Approach with Safety Guarantees,

Reference 20

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Observation 15b2146f-5a85-47bf-8f8b-558c5f5f2d9c · outbound

This paper cites an unresolved cited work.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Unresolved cited work

Reference 21

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Observation bb755b30-1fa6-4f13-ba8a-87d10a14f013 · outbound

This paper cites Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance,

Reference 22

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Observation 302a6fc2-8347-4604-92b8-9b98703d4e9c · outbound

This paper cites Recent advances in reinforcement learning-based autonomous driving behavior planning: A survey,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Recent advances in reinforcement learning-based autonomous driving behavior planning: A survey,

Reference 23

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Observation 8898c395-8e19-482a-88be-53b3dc6cb241 · outbound

This paper cites A Preference- Based Multi- Agent Federated Reinforcement Learning Algorithm Framework for Trustworthy Interactive Urban Autonomous Driving,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies A Preference- Based Multi- Agent Federated Reinforcement Learning Algorithm Framework for Trustworthy Interactive Urban Autonomous Driving,

Reference 24

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This paper cites Boosting Offline Reinforcement Learning for Autonomous Driving with Hierarchical Latent Skills,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Boosting Offline Reinforcement Learning for Autonomous Driving with Hierarchical Latent Skills,

Reference 26

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This paper cites Event-Triggered Model Predictive Control with Deep Reinforcement Learning for Autonomous Driving,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Event-Triggered Model Predictive Control with Deep Reinforcement Learning for Autonomous Driving,

Reference 27

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Observation f9e543e6-17f9-4048-8b83-fc4636fb4c2d · outbound

This paper cites Self -Learned Autonomous Driving at Unsignalized Intersections: A Hierarchical Reinforced Learning Approach for Feasible Decision-Making,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Self -Learned Autonomous Driving at Unsignalized Intersections: A Hierarchical Reinforced Learning Approach for Feasible Decision-Making,

Reference 29

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This paper cites Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving

Reference 30

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Human-Guided Deep Rein forcement Learning for Optimal Decision Making of Autonomous Vehicles,

Reference 31

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Observation e714d9b8-96d3-44c9-a19a-fea23c7ce9b6 · outbound

This paper cites Reinforcement Learning from Human Feedback for Lane Changing of Autonomous Vehicles in Mixed Traffic.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Reinforcement Learning from Human Feedback for Lane Changing of Autonomous Vehicles in Mixed Traffic

Reference 32

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This paper cites Fear -Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Fear -Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving,

Reference 33

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This paper cites Efficient learning of safe driving policy via human -ai copilot optimization,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Efficient learning of safe driving policy via human -ai copilot optimization,

Reference 34

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Observation 2569da4d-c42b-4acf-b70a-1db0b141d2cf · outbound

This paper cites Attention-Based Highway Safety Planner for Autonomous Driving via Deep Reinforcement Learning,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Attention-Based Highway Safety Planner for Autonomous Driving via Deep Reinforcement Learning,

Reference 35

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Robust lane change decision for autonomous vehicles in mixed traffic: A safety-aware multi- agent adversarial reinforcement learning approach,

Reference 36

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This paper cites An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models,

Reference 38

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This paper cites Robust Decision Making for Autonomous Vehicles at Highway On -Ramps: A Constrained Adversarial Reinforcement Learning Approach,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Robust Decision Making for Autonomous Vehicles at Highway On -Ramps: A Constrained Adversarial Reinforcement Learning Approach,

Reference 39

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Ro bust Lane Change Decision Making for Autonomous Vehicles: An Observation Adversarial Reinforcement Learning Approach,

Reference 41

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Unresolved cited work

Reference 42

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This paper cites Adversarial Stress Test for Autonomous Vehicle Via Series Reinforcement Learning Tasks with Reward Shaping,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Adversarial Stress Test for Autonomous Vehicle Via Series Reinforcement Learning Tasks with Reward Shaping,

Reference 43

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This paper cites CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening

Reference 44

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies ATS -O2A: A state-based adversarial attack strategy on deep reinforcement learning,

Reference 45

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning,

Reference 46

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Attacking Deep Reinforcement Learning with Decoupled Adversarial Policy,

Reference 47

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Large Language Model guided Deep Reinforcement Learning for Decision Making in Autonomous Driving

Reference 48

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This paper cites Safe Driving via Expert Guided Policy Optimization,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Safe Driving via Expert Guided Policy Optimization,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:56:36.482474Z

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This paper cites Efficient Deep Reinforcement Learning With Imitative Expert Priors for Autonomous Driving,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Efficient Deep Reinforcement Learning With Imitative Expert Priors for Autonomous Driving,

Reference 50

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Measuring Robustness to Natural Distribution Shifts in Image Classification,

Reference 51

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Observation 9092fd49-3e8f-4d5d-bf33-dfad048c915b · outbound

This paper cites Stable- baselines3: Reliable reinforcement learning implementations,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Stable- baselines3: Reliable reinforcement learning implementations,

Reference 52

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Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Adaptive Mixtures of Local Experts,

Reference 53

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Observation d96e01f9-83fd-45e3-9e3d-a420b062d60c · outbound

This paper cites an unresolved cited work.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:56:36.409826Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d8a25aba-3119-4757-8a42-74924023118a · outbound

This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:56:36.387476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 59274537-557b-46f6-8d5b-51e5f2cfcb86 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Proximal Policy Optimization Algorithms

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T18:56:33.528103Z

Source-reported events for the cited work

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Observation 7e891b41-4a91-46f2-adad-fb3ecb4c05fe · outbound

This paper cites Energy- Constrained Safe Path Planning for UAV- Assisted Data Collection of Mobile IoT Devices,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Energy- Constrained Safe Path Planning for UAV- Assisted Data Collection of Mobile IoT Devices,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T18:56:33.535019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 446fa816-f283-44b4-9745-82ab8e8fed96 · outbound

This paper cites Soft Actor-Critic: Off- Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Soft Actor-Critic: Off- Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T18:56:33.541356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b48263d4-3f0b-47b5-8262-2017ddfce80c · outbound

This paper cites Addressing Function Approximation Error in Actor-Critic Methods,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Addressing Function Approximation Error in Actor-Critic Methods,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T18:56:33.546825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b41572be-10d5-46e1-9417-d16a6dd05a29 · outbound

This paper cites Hybrid Policy Optimization from Imperfect Demonstrations.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Hybrid Policy Optimization from Imperfect Demonstrations

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:56:36.317456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 48565531-8f4a-40e3-b435-95cc3700edd0 · outbound

This paper cites Explainable Deep Adversarial Reinforcement Learning Approach for Robust Autonomous Driving,.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Explainable Deep Adversarial Reinforcement Learning Approach for Robust Autonomous Driving,

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T18:56:33.563827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2edd9515-e5eb-4ebc-acf8-4ee99160bdb8 · outbound

This paper cites Adversarial examples in the physical world.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Adversarial examples in the physical world

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T18:56:33.569294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 187756f9-232b-48d6-97a0-1953725993e3 · outbound

This paper cites [Online].

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies [Online]

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:56:36.365838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0eb340f7-cae1-4fd7-8331-db578031af72 · outbound

This paper cites Available: https://proceedings.neurips.cc/paper_files/paper/2020/hash/d8330f857a 17c53d217014ee776bfd50-Abstract.html.

Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies Available: https://proceedings.neurips.cc/paper_files/paper/2020/hash/d8330f857a 17c53d217014ee776bfd50-Abstract.html

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:56:36.435780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 95ae24ad-af80-4897-9669-998938547369 · inbound

Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach cites this paper.

Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach Sharpening the Spear: Adaptive Expert-Guided Adversarial Attack Against DRL-based Autonomous Driving Policies

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T10:43:05.773872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.