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Paper Citation Record · LEDGER

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing

As of 13 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2411.13755.

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

pith.paper-citation-record.v1
2411.13755 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:16:46.824719Z

measured 28 of 28 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

28 of 28 outbound references displayed

  • verified exact3
  • verified fuzzy17
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b3fec3b-6c1e-4e0a-a6e0-d1e4b278a37b · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Optuna: A next-generation hyperparameter optimization framework

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.715123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.715123Z digest=sha256:370431da57f660697bb505f62d2382ec2fecb3d4d431c808346d90084d2b20e7

Observation aeedf9ef-31a0-465c-9551-542dbc797a56 · outbound

This paper cites Commonroad: Composable benchmarks for motion planning on roads.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Commonroad: Composable benchmarks for motion planning on roads

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.237155Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.719518Z digest=sha256:0bd62782f2763a639091eb179f3944d262f18e219446e42df64f4cca20b420be

Observation 5517cc13-bd4c-4e5c-b5b6-b52fff390483 · outbound

This paper cites Kernels for vector-valued functions: A review.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Kernels for vector-valued functions: A review

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.723894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.723894Z digest=sha256:d3c0ec879ce122ace8b671e5b49a9ca936866eea499c072fe4edc899c952a5bf

Observation b1ad5bb0-e7e1-4dec-bde8-8b07ad3d88af · outbound

This paper cites an unresolved cited work.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-12T16:16:48.219827Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.728087Z digest=sha256:ebdce5cda0a5c4d9ae4d500c62c0ef06cb050569a2368c655e55821296da1996

Observation 7e0da50f-4163-494f-8faf-508821179da7 · outbound

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

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Autonomous vehicles on the edge: A survey on autonomous vehicle racing

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.207904Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.731892Z digest=sha256:6486fa8f0c846867386cbf9abb6ba34e7fbc61a2692f77827081c3bd19c6c182

Observation 9085036d-454f-4df8-96e0-57eca89add66 · outbound

This paper cites Experiment tracking with weights and biases, 2020.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Experiment tracking with weights and biases, 2020

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.735519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.735519Z digest=sha256:c141ffecc9815380fdb2752cbdffebb14d7145b58239538b05fea368d99a6527

Observation 38f040e8-b473-40ca-8aea-b325488d51fd · outbound

This paper cites Efficient implementation of randomized mpc for miniature race cars.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Efficient implementation of randomized mpc for miniature race cars

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.189416Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.739341Z digest=sha256:db12b9bfc920199d1e088ea2341aa7b41f0161e602707011ef4e0b16304870a6

Observation d16a5a7b-1e61-4323-a2b1-41b18e179957 · outbound

This paper cites Deep dynamics: Vehicle dynamics modeling with a physics-constrained neural network for autonomous racing.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Deep dynamics: Vehicle dynamics modeling with a physics-constrained neural network for autonomous racing

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.177568Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.742759Z digest=sha256:2402333f1331266e8ba2276cd86af985f5e6d6a171e7d4c96a6d8fb20066b0fd

Observation 80bb327c-da45-4107-84b3-0d6c5c63a019 · outbound

This paper cites Modelling longitudinal vehicle dynamics with neural networks.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Modelling longitudinal vehicle dynamics with neural networks

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.168001Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.746268Z digest=sha256:be030a56e51cfaeba1e3b22512d48ca91f8e32fd4492017a6d5550b556b8df4c

Observation 228bdcf7-4832-482f-8fca-afd45bbfc621 · outbound

This paper cites Competitive Driving of Autonomous Vehicles.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Competitive Driving of Autonomous Vehicles

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-12T16:16:48.005321Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.750183Z digest=sha256:714407f69c17609624154536c080ce085fbf85286a4869c2d6bd7d4865e369bc

Observation 0d6bfac6-af3d-45a0-babe-265bd5fd10de · outbound

This paper cites End-to-end neural network for vehicle dynamics modeling.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing End-to-end neural network for vehicle dynamics modeling

Reference 11

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-12T16:16:47.990183Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.754287Z digest=sha256:e80fe29c11191457e80579f050d9da7c2a8f2b30f58b6ddbbdf6d9e1792d019a

Observation 8e59caf7-6c56-4a7f-b26c-6769d4001bd1 · outbound

This paper cites Bayesrace: Learning to race autonomously using prior experience.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Bayesrace: Learning to race autonomously using prior experience

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.157204Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.758077Z digest=sha256:dbfffe9f33a40dd4b85bf134ecd4cf2bef21f0a0d382af519e62fa43480250f3

Observation d8e1f38e-c78d-462c-ace9-11e893499ec6 · outbound

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

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Learning-based model predictive control for autonomous racing

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.146161Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.761789Z digest=sha256:d2c8df17b82cfe8d06d03409a5b4b0daa3439f8970b54f4755c0289ad4cc470d

Observation b810ddb8-a541-46c8-94ad-7eced8aae195 · outbound

This paper cites Racecar-the dataset for high-speed autonomous racing.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Racecar-the dataset for high-speed autonomous racing

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.135590Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.765105Z digest=sha256:e89121d69dab72eda63606d477baa44dbe6042018293b870306bc190684de837

Observation 9c4ed46e-da7d-41af-b5ed-fcbd4e8d0849 · outbound

This paper cites Optimization-based autonomous racing of 1: 43 scale rc cars.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Optimization-based autonomous racing of 1: 43 scale rc cars

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.124396Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.768556Z digest=sha256:250c0e841efc17bcde17fcd27bae22e28ff457d5042ddb98b0c18953e9de0366

Observation 167b6454-fd91-40bb-bfed-d9c1e9fb405f · outbound

This paper cites Scalable deep kernel gaussian process for vehicle dynamics in autonomous racing.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Scalable deep kernel gaussian process for vehicle dynamics in autonomous racing

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.112642Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.772117Z digest=sha256:119981bec53af25cf044bcbdca9ce25d91d49a45284a0ce6155aa655cd3baee8

Observation 9a60cfc8-21b0-492b-aa20-e8b40d62594d · outbound

This paper cites Vehicle Dynamics Modeling for Autonomous Racing Using Gaussian Processes.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Vehicle Dynamics Modeling for Autonomous Racing Using Gaussian Processes

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-12T16:16:46.898260Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.775919Z digest=sha256:0b81b7bdbe4d25716216dde0229c8d0750c07fe283e4a46ae2e64d027ac222a2

Observation 024a0d72-f492-4a50-be08-ebf40352720c · outbound

This paper cites Gaussian processes for vehicle dynamics learning in autonomous racing.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Gaussian processes for vehicle dynamics learning in autonomous racing

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.098759Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.780008Z digest=sha256:5481ab47a8029c86749b66a650224f639336b75f8b24c5768c392c2b76711179

Observation 56ff2926-9658-4b54-8fc2-807e8b9cb317 · outbound

This paper cites F1/10: An Open-Source Autonomous Cyber-Physical Platform.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing F1/10: An Open-Source Autonomous Cyber-Physical Platform

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.783855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.783855Z digest=sha256:58c12107dcb6930db80cc1d7b984573a8ca99acc1ae2455ef12c689b13f98a91

Observation 2b0f122c-80ad-4627-bc10-6b3c94e5913c · outbound

This paper cites Tire and vehicle dynamics.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Tire and vehicle dynamics

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.088033Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.789347Z digest=sha256:bf10ab77f664c2f458a0f97a94b87f353292d5fc5ba71e888294a895645131b9

Observation 09b2dd6a-de96-461f-841c-ae36e93bab18 · outbound

This paper cites Data-driven vehicle modeling of longitudinal dynamics based on a multibody model and deep neural networks.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Data-driven vehicle modeling of longitudinal dynamics based on a multibody model and deep neural networks

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.076063Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.793587Z digest=sha256:270ec58e0e1d9a0dd9f0601f84b27320dcba8f462d376562ad9b81c64335aba7

Observation a2055444-9992-4f99-907f-2778a2294903 · outbound

This paper cites Motion planning and control for multi vehicle autonomous racing at high speeds.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Motion planning and control for multi vehicle autonomous racing at high speeds

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.064029Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.798573Z digest=sha256:ba2bedb5c53238ec9878c331f38048c6db7fa4cbf6c461cd99fc04e8b60a53ee

Observation fb561a2c-8147-4a46-92d8-6d3c575fc283 · outbound

This paper cites Gaussian processes in machine learning.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Gaussian processes in machine learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.802838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.802838Z digest=sha256:c3684986596ec6a6067134ec51d6c2eb410bb9441d8f31eaf8d5e2408fdc0a50

Observation 82269007-a693-4b68-a610-d984c30dc5a2 · outbound

This paper cites Online constrained model-based reinforcement learning.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Online constrained model-based reinforcement learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.046687Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.807010Z digest=sha256:5100f06aef3660adfa20f59cf8607a259b172be7c4b3ec8612ff5525912dd846

Observation a0310679-0855-4f9a-859e-34fbea40016f · outbound

This paper cites Graphical models, exponential families, and variational inference.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Graphical models, exponential families, and variational inference

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.812057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.812057Z digest=sha256:45716e14bfe1c60ccdde5b4481e50f8df2dfa7c9633f118a82e5dff8055be4e6

Observation 9c5d41cf-c955-43ec-bf29-6269e5a31774 · outbound

This paper cites DeepRacing: Parameterized Trajectories for Autonomous Racing.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing DeepRacing: Parameterized Trajectories for Autonomous Racing

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:46.816868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:16:46.816868Z digest=sha256:792a3af3a369b594921715ff1e6f5994f10ec85cff56173b6c95a1f466a32581

Observation e95aff74-956c-4cbe-ad54-ed3ee0d97710 · outbound

This paper cites Deep kernel learning.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Deep kernel learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.028940Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.820970Z digest=sha256:8579cd3ae5d01047e1f2f78d09a1ad09387b7a464776da7fa87a15429e66d6db

Observation 2b9a8498-fe07-4524-9bfd-25d594078ee5 · outbound

This paper cites Indy autonomous challenge-autonomous race cars at the handling limits.

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Indy autonomous challenge-autonomous race cars at the handling limits

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T16:16:48.017457Z

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.

source=arxiv_source observed=2026-08-12T16:16:46.824719Z digest=sha256:2ecae9104652c211f2dfb71cac12980bfe7ae56ccaf3c076b488143af8a03195

Pith citing papers

No inbound Pith citation observations are available.