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Paper Citation Record · LEDGER

New Scheme Adaption Strategy for Hyperbolic Conservation Laws

As of 18 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2604.09498.

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

pith.paper-citation-record.v1
2604.09498 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T23:09:48.353960Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

36 of 36 outbound references displayed

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  • unresolved36
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0b821b3-ea35-473b-a272-eeeefa9179dd · outbound

This paper cites Autonomous vehicles on the edge: A survey on autonomous vehicle racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Autonomous vehicles on the edge: A survey on autonomous vehicle racing,

Reference 1

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:46b550164ce0dc0034241d738effe8c51325aecf3378be8f6f48f26aaef84428

Observation f6cdef2f-8cd8-453b-8944-fcd5409ebe10 · outbound

This paper cites Tinyl- idarnet: 2d lidar-based end-to-end deep learning model for f1tenth autonomous racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Tinyl- idarnet: 2d lidar-based end-to-end deep learning model for f1tenth autonomous racing,

Reference 2

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Observation fae892e7-bc50-49a2-bdbd-23bc83a39a4e · outbound

This paper cites RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms

Reference 3

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Observation 90f82212-21a5-4db0-b8db-3431285cfcd3 · outbound

This paper cites Comparing deep reinforcement learning architectures for autonomous racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Comparing deep reinforcement learning architectures for autonomous racing,

Reference 4

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Observation 4789bdf7-eaae-4fb8-b905-079368e264b4 · outbound

This paper cites Latent imagination facilitates zero-shot transfer in autonomous racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Latent imagination facilitates zero-shot transfer in autonomous racing,

Reference 5

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Observation 4d3d4fab-6d92-4c8b-9f43-6b00befdc257 · outbound

This paper cites Train in Austria, race in Montecarlo: Generalized RL for cross-track F1 tenth lidar-based races,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Train in Austria, race in Montecarlo: Generalized RL for cross-track F1 tenth lidar-based races,

Reference 6

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:ce4cb4eba1497a8d7b387b7b78b1215d3301f00299792ab8c23f613ac678596d

Observation 9cf1745b-e833-44ed-9d0c-497bd6cb900e · outbound

This paper cites Super- human performance in gran turismo sport using deep reinforcement learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Super- human performance in gran turismo sport using deep reinforcement learning,

Reference 7

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:54b75f80562f050fb55643a0a8312b4addf136847192b2671aa6c99702c18ba9

Observation 265f44c0-7338-4a19-98b8-c68b9e22b003 · outbound

This paper cites Bypassing the Simulation-to-reality Gap: Online Reinforcement Learning using a Supervisor.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Bypassing the Simulation-to-reality Gap: Online Reinforcement Learning using a Supervisor

Reference 8

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:ed11a8264015280a540c037c8c5e266f3c063874a8e0be73f1203af01e46e185

Observation 585715aa-b1cb-42cd-961e-c39854ec1492 · outbound

This paper cites Minimum curvature trajectory planning and control for an autonomous race car,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Minimum curvature trajectory planning and control for an autonomous race car,

Reference 9

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:0333e44ba2ae0c4c5522fe430e0e6c015cc249bbfef658d9e8a4ee75030dfb73

Observation 77ea215a-82f0-48a1-81a9-640dcd862f7f · outbound

This paper cites Nonlinear model predictive control for optimal motion planning in autonomous race cars,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Nonlinear model predictive control for optimal motion planning in autonomous race cars,

Reference 10

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:4561a036c447a5217534224e7688a370439ad344dd1bbd6a34a3a82e078c9bdf

Observation f0e019fa-9fc9-4e6d-837f-6f9bea1f8636 · outbound

This paper cites F1tenth: An open-source evaluation environment for continuous control and reinforcement learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws F1tenth: An open-source evaluation environment for continuous control and reinforcement learning,

Reference 11

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:1c934511facf8e1f1aba960d2890b5e735707a00884d811103237c16481ae924

Observation 98c3c655-5a6b-44d7-8b16-f3d6a22073b3 · outbound

This paper cites Advancing autonomous racing: A comprehensive survey of the roboracer (f1tenth) platform,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Advancing autonomous racing: A comprehensive survey of the roboracer (f1tenth) platform,

Reference 12

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:6435d539c4931b331c3d3a3d74dade227161cc69c4d78a2f9c74901f8167b509

Observation f892c7d0-2fe4-49e1-8939-f832d1625026 · outbound

This paper cites Proximal Policy Optimization Algorithms.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Proximal Policy Optimization Algorithms

Reference 13

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Observation fa8c6937-9619-4144-b93c-a4ad14fdff4a · outbound

This paper cites Xtenth-car: A proportionally scaled experimental vehicle platform for connected autonomy and all-terrain research,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Xtenth-car: A proportionally scaled experimental vehicle platform for connected autonomy and all-terrain research,

Reference 14

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:918057a7d30298add3daba0be56ae6962908f0edd35fd429410c1efe441cdda4

Observation 0efafbe1-cfaa-4dd3-a4d8-9b66f13eade1 · outbound

This paper cites Racemop: Mapless online path planning for multi-agent autonomous racing using residual policy learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Racemop: Mapless online path planning for multi-agent autonomous racing using residual policy learning,

Reference 15

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:4e03b4f99bb262da50d36231dadf8ab66f126e27e443730655ea9dba4df4cb8e

Observation 4cfb995c-3bdf-48c3-b885-4e8680fecb7e · outbound

This paper cites Tyre modelling for use in vehicle dynamics studies,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Tyre modelling for use in vehicle dynamics studies,

Reference 16

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:5245f4154ae8ce97cb2fc7ecbf947378e948394e4241a41c01c21dc6b0bec09c

Observation 14e6aea0-5623-4a4b-a4bc-8affd4416861 · outbound

This paper cites The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?

Reference 17

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:f01163aa167cf5757f84fc2a21b4e3616b4ba94574c57cd50eacc229e6817499

Observation e15bce65-b347-46b1-a0fe-4dad220a22a9 · outbound

This paper cites Optimization-based au- tonomous racing of 1: 43 scale rc cars,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Optimization-based au- tonomous racing of 1: 43 scale rc cars,

Reference 18

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:a4ad344e05f2a99548a4f2ae59928d267abcab23d1bcf95812f4bb05ccb40761

Observation 903ff3cd-3307-4f3c-8483-10af3c63fe22 · outbound

This paper cites High-speed autonomous racing using trajectory-aided deep reinforcement learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws High-speed autonomous racing using trajectory-aided deep reinforcement learning,

Reference 19

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:e8532468a37c1e2d6da98b15f93c44914c9b5ff9e00f2ae9cc0e1488a679e3c9

Observation 14d8bfa0-8949-4a66-a4b1-ba44c03375fb · outbound

This paper cites Tum autonomous motorsport: An autonomous racing software for the indy autonomous challenge,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Tum autonomous motorsport: An autonomous racing software for the indy autonomous challenge,

Reference 20

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Observation 9d7b5877-e07c-42e0-933f-0ef05182113a · outbound

This paper cites Learning-based model predictive control for autonomous racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Learning-based model predictive control for autonomous racing,

Reference 21

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Observation a1522397-3483-4920-a79c-b1d797433dad · outbound

This paper cites Piecewise affine relaxation of discrete value functions in learning model predictive control with application to autonomous racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Piecewise affine relaxation of discrete value functions in learning model predictive control with application to autonomous racing,

Reference 22

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Observation 09b1d1cd-9f3d-432b-8493-f917a5bb56f5 · outbound

This paper cites Online learning of mpc for autonomous racing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Online learning of mpc for autonomous racing,

Reference 23

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:35777abe2cdd71ac630559a22ed9f32650852192455470cde39759ccec793d38

Observation 189dfe32-4ceb-4133-a44d-ae444a3e37dc · outbound

This paper cites Optimization-based hierarchical motion planning for autonomous rac- ing,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Optimization-based hierarchical motion planning for autonomous rac- ing,

Reference 24

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Observation 510221c2-8005-4c18-b83b-7f261697462f · outbound

This paper cites A nonlinear model predictive control strategy for autonomous racing of scale ve- hicles,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws A nonlinear model predictive control strategy for autonomous racing of scale ve- hicles,

Reference 25

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:6b9592306933be4af358b10295dff7291fcbb8fb386d0aaef57848c994440274

Observation 40f3dc89-c7ab-40e2-a48a-3e7ebd6891d0 · outbound

This paper cites Champion-level drone racing using deep reinforcement learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Champion-level drone racing using deep reinforcement learning,

Reference 26

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:7ff3b293e4400c14a2fbcdd03fa895fa77427fc110271d9de61cf80b6b1658d4

Observation ced7fe51-df2a-48e6-877f-066855d44388 · outbound

This paper cites Learning from simulation, racing in reality,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Learning from simulation, racing in reality,

Reference 27

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:75b2084da299c2bf510583f2af57bf8ff5a241fd2e74af0d9ecd6e77b6982284

Observation 60b29183-2bd3-48ba-a2c3-f5b58d3cf5e1 · outbound

This paper cites Autodrive simulator: A simulator for scaled autonomous vehicle research and education,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Autodrive simulator: A simulator for scaled autonomous vehicle research and education,

Reference 28

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:85439dc78510f3e16b9dd8e439e204f188482b9e76d88e97c6f4b01eb91fe783

Observation e09e1d19-3a44-453f-bc4b-d1b8c0409ed2 · outbound

This paper cites OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction

Reference 29

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:72492c627f0e99772b65f60bf557bf1eef3761cf285d13842ea4a49ecfc76aa5

Observation 94e54dfc-dfac-4e63-abb8-3cbccb69cabf · outbound

This paper cites BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion

Reference 30

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:ba97af8afb94fe4d3f06b7fac103e09318d3ea1e63a4a3def91e2bfcae21cd7d

Observation f7306811-0a56-48c0-9688-e29087b8d8b6 · outbound

This paper cites Viral: Visual sim-to-real at scale for humanoid loco-manipulation,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Viral: Visual sim-to-real at scale for humanoid loco-manipulation,

Reference 31

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:b9aae4c76180b4f207f8bfc5ba93df515752c447f6c210d7b571867ede35ff39

Observation 16cd676c-acd2-4a2d-81ed-cacbdc0253b2 · outbound

This paper cites Ame-2: Agile and gen- eralized legged locomotion via attention-based neural map encoding,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Ame-2: Agile and gen- eralized legged locomotion via attention-based neural map encoding,

Reference 32

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:ff7faa4538071e4d614ddc5a19e3bed7c06a5aa181187be9ace1cce3c28c24dd

Observation 161cb248-9b4a-4ba7-a6b3-3289aa1add26 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Soft Actor-Critic Algorithms and Applications

Reference 33

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:bc95f159d9336e37f6d5ba134fd1d5cb64a081755c40053fb523d08acf2b6ad5

Observation 498fc646-968e-4ad4-a1fc-75ee290b8d00 · outbound

This paper cites Autovrl: A high fidelity autonomous ground vehicle simulator for sim-to-real deep rein- forcement learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Autovrl: A high fidelity autonomous ground vehicle simulator for sim-to-real deep rein- forcement learning,

Reference 34

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:f130357c334d718c634574837a8644ac88cb564681d2370d69903af0c11e1196

Observation 3c1f2f8d-7bb7-4919-a106-6d8554ac0b50 · outbound

This paper cites Pybullet, a python module for physics simulation for games, robotics and machine learning,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Pybullet, a python module for physics simulation for games, robotics and machine learning,

Reference 35

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:a8aa7a5429d9a8c8c46648e0e07e5830a396301580533dc437e98cbaba80f6a0

Observation 59336b42-be77-4b75-bf20-56b23e82f538 · outbound

This paper cites Dream to control: Learning behaviors by latent imagination,.

New Scheme Adaption Strategy for Hyperbolic Conservation Laws Dream to control: Learning behaviors by latent imagination,

Reference 36

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source=pdf_text observed=2026-07-12T23:09:48.353960Z digest=sha256:bf8c8ff254863a87c016b15834b8ac0a61c9f50d54b1df21910a2d8e6f9e792b

Pith citing papers

No inbound Pith citation observations are available.