Paper Citation Record · LEDGER

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 3 inbound Pith citation observations for arXiv:2501.12296.

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

pith.paper-citation-record.v1
2501.12296 v3

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:22:32.157863Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:18:53.079168Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T13:38:19.098731Z

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy23
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 84a8b9ec-b0f1-4dab-ac08-40e1a3c441c1 · outbound

This paper cites Development and testing of an image transformer for explainable autonomous driving systems[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Development and testing of an image transformer for explainable autonomous driving systems[J]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.618117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 14d8463e-f445-4dbc-8e92-2bb9e0d5ba2c · outbound

This paper cites Explainable artificial intel- ligence for autonomous driving: A comprehensive overview and field guide for future research directions[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Explainable artificial intel- ligence for autonomous driving: A comprehensive overview and field guide for future research directions[J]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.603885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e3db5924-c655-498a-8863-5fa6120081a1 · outbound

This paper cites Recent advancements in end-to-end autonomous driving using deep learning: A survey[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Recent advancements in end-to-end autonomous driving using deep learning: A survey[J]

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.591969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8aa3b580-046d-45bf-be60-f504ae9d9b80 · outbound

This paper cites A survey on multimodal large language models for autonomous driving[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning A survey on multimodal large language models for autonomous driving[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.579989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation afe2604f-550a-4207-848d-f7cc43dcb603 · outbound

This paper cites Monolayout: Amodal scene layout from a single image[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Monolayout: Amodal scene layout from a single image[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.568317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59cdb103-dfa9-42b8-8831-ea52ec643dfc · outbound

This paper cites an unresolved cited work.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:22:32.557568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d618bbb7-7770-4ce2-a225-e1a3e26e8947 · outbound

This paper cites an unresolved cited work.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:22:32.545406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2d4e0abe-41b4-40d7-91e1-3e747d75ed8e · outbound

This paper cites Deep learning-based image 3-d object detection for autonomous driving[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Deep learning-based image 3-d object detection for autonomous driving[J]

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.531945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5d3fa7ed-e42b-4573-9674-253f208eb3a8 · outbound

This paper cites Transformation-equivariant 3d object detec- tion for autonomous driving[C]//Proceedings of the AAAI Conference on Artificial Intelligence.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Transformation-equivariant 3d object detec- tion for autonomous driving[C]//Proceedings of the AAAI Conference on Artificial Intelligence

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.517972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cfdf52f3-d3c6-4bba-ab0e-841c30c214eb · outbound

This paper cites Planning-oriented autonomous driv- ing[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Planning-oriented autonomous driv- ing[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.505045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62b19f18-cb82-4b37-a05e-62f5f6e98d76 · outbound

This paper cites Vision meets robotics: The kitti dataset[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Vision meets robotics: The kitti dataset[J]

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.492981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4d075d0f-f48f-4b72-89f5-1e32b4cf3411 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Scalability in perception for autonomous driving: Waymo open dataset[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.480522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 30e65f0c-ee27-46bd-a8cc-6f4d9ddfbcab · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning nuscenes: A multimodal dataset for autonomous driving[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.466692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 54774770-5b3f-440c-84d7-64aaa45e87b7 · outbound

This paper cites Towards corner case detection for autonomous driving[C]//2019 IEEE Intelligent vehicles symposium (IV).

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Towards corner case detection for autonomous driving[C]//2019 IEEE Intelligent vehicles symposium (IV)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.452284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8900cdc-85b9-4747-847e-50343b053ec7 · outbound

This paper cites Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approaches.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approaches

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T17:22:32.083297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76365674-08e9-40c4-9f68-24145c87d9f0 · outbound

This paper cites Coda: A real-world road corner case dataset for object detection in autonomous driving[C]//European Conference on Computer Vision.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Coda: A real-world road corner case dataset for object detection in autonomous driving[C]//European Conference on Computer Vision

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.436686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9a336b2a-f999-4f16-8cc2-343d54e4d29f · outbound

This paper cites How simulation helps autonomous driving: A survey of sim2real, digital twins, and parallel intelligence[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning How simulation helps autonomous driving: A survey of sim2real, digital twins, and parallel intelligence[J]

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.422838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b6cc60c1-7bc6-45b9-bd19-f2e1483076c7 · outbound

This paper cites Retrieval-augmented multiple instance learning[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Retrieval-augmented multiple instance learning[J]

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.408707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8702f46d-f616-40c0-b520-e6ea89e0a8bb · outbound

This paper cites an unresolved cited work.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:22:32.394736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 57e23513-36c1-4e45-a44f-ed3c811dae83 · outbound

This paper cites Monocular 3d object detection for autonomous driving.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Monocular 3d object detection for autonomous driving

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.381884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4cf93fa3-7d1f-4913-9d34-0b396ab7fab0 · outbound

This paper cites CornerSim: A Virtualization Frame- work to Generate Realistic Corner-Case Scenarios for Autonomous Driving Perception Testing[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning CornerSim: A Virtualization Frame- work to Generate Realistic Corner-Case Scenarios for Autonomous Driving Perception Testing[J]

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.368614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6df68bb8-6634-45b6-9695-d03788464d87 · outbound

This paper cites Yottixel–an image search engine for large archives of histopathology whole slide images.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Yottixel–an image search engine for large archives of histopathology whole slide images

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.354287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d6e6665a-444b-4196-9fad-6f21b40c01a3 · outbound

This paper cites Fast and scalable search of whole-slide images via self-supervised deep learning.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Fast and scalable search of whole-slide images via self-supervised deep learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.341267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3430add6-440f-4349-8ab1-e8f9cd3c96f6 · outbound

This paper cites Hierarchical Optimal Transport for Comparing Histopathology Datasets.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Hierarchical Optimal Transport for Comparing Histopathology Datasets

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T17:22:32.120944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e1520a3-9ad5-4450-ac8d-f3a534c968c3 · outbound

This paper cites MRFP: Learning Generalizable Semantic Segmen- tation from Sim-2-Real with Multi-Resolution Feature Perturbation.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning MRFP: Learning Generalizable Semantic Segmen- tation from Sim-2-Real with Multi-Resolution Feature Perturbation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.326604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c706503e-6f98-457b-8588-33d5d40b8a68 · outbound

This paper cites Sim2real predictivity: Does evaluation in simulation predict real-world performance?,.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Sim2real predictivity: Does evaluation in simulation predict real-world performance?,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.313129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9f24ab25-9c33-4970-8a72-04fd15ebd71b · outbound

This paper cites an unresolved cited work.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:22:32.299303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aca82045-2cc2-4fd6-9af3-8c779b980431 · outbound

This paper cites SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-10T17:22:32.203947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c6c330fc-e643-45dd-ae79-fc35f708dc83 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Sinkhorn distances: Lightspeed computation of optimal transport

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T17:22:32.144510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1406c7ae-f876-4bd1-96f8-9057245a4167 · outbound

This paper cites an unresolved cited work.

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:22:32.275283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9767d963-73bd-4866-afa7-5218d866a1a1 · outbound

This paper cites Testing and certification of automated vehicles (A V) includ- ing cybersecurity and artificial intelligence aspects[J].

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning Testing and certification of automated vehicles (A V) includ- ing cybersecurity and artificial intelligence aspects[J]

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.261929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ac2551b9-d45c-42d2-a72e-0994910b246d · outbound

This paper cites E2e parking: Autonomous parking by the end-to-end neural network on the carla simulator[C]//2024 IEEE Intelligent Vehicles Symposium (IV).

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning E2e parking: Autonomous parking by the end-to-end neural network on the carla simulator[C]//2024 IEEE Intelligent Vehicles Symposium (IV)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:22:32.248617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 84a31224-8397-4c51-b987-756b1983f46a · inbound

RealDrive: Retrieval-Augmented Driving with Diffusion Models cites this paper.

RealDrive: Retrieval-Augmented Driving with Diffusion Models RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T12:18:53.079168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50c62779-7b15-42d4-afaa-5f8f1bccca1c · inbound

CARD: A Multi-Modal Automotive Dataset for Dense 3D Reconstruction in Challenging Road Topography cites this paper.

CARD: A Multi-Modal Automotive Dataset for Dense 3D Reconstruction in Challenging Road Topography RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

Reference 64

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:40:42.691333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5beeb5f0-c03b-4b47-91d9-9d225b952f50 · inbound

Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions cites this paper.

Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:38:19.100681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.