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Paper Citation Record · LEDGER

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

As of 18 August 2026, this Paper Citation Record lists 100 of 117 outbound references and 8 inbound Pith citation observations for arXiv:2412.09647.

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

pith.paper-citation-record.v1
2412.09647 v1

Coverage vector

measured 100 of 117 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:16:00.746423Z

measured 108 of 108 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:12:11.217599Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T03:24:28.718453Z

Reference resolution

100 of 117 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved95
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 05423f8a-5808-4936-8573-ad3501be4b68 · outbound

This paper cites Delphi: Efficient Asynchronous Approximate Agreement for Distributed Oracles.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Delphi: Efficient Asynchronous Approximate Agreement for Distributed Oracles

Reference 1

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T18:16:00.314876Z digest=sha256:341ab0dda3f938f8d70a96ad2a4b364ab544812c07feb580f64a1438332546a7

Observation f0cad54d-9814-4545-853f-7fa3bf21df2c · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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source=pdf_text observed=2026-08-11T18:16:00.320391Z digest=sha256:ef0d08147d1eec63119e6631fbb7704e67561073aa15371b5eb03e1a72b6b066

Observation 1f9365bc-4359-4cd1-8a1f-52012f82f1b6 · outbound

This paper cites Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models

Reference 3

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source=pdf_text observed=2026-08-11T18:16:00.324776Z digest=sha256:b116f985e604fd8fb7b52c8ea476830b8fa0e91366668c8a1f2ac0adb7bdc954

Observation 8323f484-be29-4915-9f08-c4129987a492 · outbound

This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom

Reference 4

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source=pdf_text observed=2026-08-11T18:16:00.329347Z digest=sha256:c8994795f52188924d9cd0d81605b62fdee50750d407849de738d317bab91029

Observation 8d5e3a14-2d36-4f6f-81fa-3f194a5d2cd0 · outbound

This paper cites Learning from all ve- hicles.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Learning from all ve- hicles

Reference 5

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source=pdf_text observed=2026-08-11T18:16:00.333289Z digest=sha256:ac1fa4a178f4efaa059af6c244b20d8ad42fca6fa36bc41061d7b5fab2241e52

Observation b1ce422e-ba2f-4701-96f1-80abe8147405 · outbound

This paper cites Learning by cheating.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Learning by cheating

Reference 6

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source=pdf_text observed=2026-08-11T18:16:00.337773Z digest=sha256:5968c7a580ac760ff61488bee692128f9f5f02f8bac2a6ead5545eccf9799024

Observation 67900954-4848-4116-9613-d245c6720cb5 · outbound

This paper cites Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering

Reference 7

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source=pdf_text observed=2026-08-11T18:16:00.342453Z digest=sha256:3b4f8f30e8b9bf8a1865c65fb5c65ee28604d93821a091b08d40104f6f8b4b08

Observation 4a702300-132f-4a6c-a656-b8d2462fe727 · outbound

This paper cites OmniRe: Omni Urban Scene Reconstruction.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model OmniRe: Omni Urban Scene Reconstruction

Reference 8

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source=pdf_text observed=2026-08-11T18:16:00.347439Z digest=sha256:f7fe76cc8b4616ebb4e311d2caf233ca54013fefe39ba62cc6159926099b48e7

Observation 72ba53f0-4ba3-43fa-9d74-a374ebae54c6 · outbound

This paper cites Rethinking Imitation-based Planner for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Rethinking Imitation-based Planner for Autonomous Driving

Reference 9

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source=pdf_text observed=2026-08-11T18:16:00.351836Z digest=sha256:3014f8149adc2886ec0fcfe30aae9fa366754ac9540ffbe9fe09bdf1063efbc5

Observation 88ac35c7-2fee-4903-ada8-814f670d30c7 · outbound

This paper cites Transfuser: imita- tion with transformer-based sensor fusion for autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Transfuser: imita- tion with transformer-based sensor fusion for autonomous driving

Reference 10

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source=pdf_text observed=2026-08-11T18:16:00.357340Z digest=sha256:e8701c0ab531f2c3de4079c401432821877631389f92af86c8157c6635ff5e22

Observation d3d62167-397b-40fe-be1e-f43fbbc1f053 · outbound

This paper cites Transfuser: Imita- tion with transformer-based sensor fusion for autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Transfuser: Imita- tion with transformer-based sensor fusion for autonomous driving

Reference 11

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source=pdf_text observed=2026-08-11T18:16:00.361593Z digest=sha256:97297cb3e0f0255760875960e1758213c7e71a056094d5334888c86ddb044142

Observation 718d6ab4-6f62-4eac-a356-e4ff8764b256 · outbound

This paper cites End-to-end driving via conditional imitation learning.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model End-to-end driving via conditional imitation learning

Reference 12

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source=pdf_text observed=2026-08-11T18:16:00.366638Z digest=sha256:eda2c8951fc452db5abdd578544d07cbb38b35d4c0c9fbd638c37091e4285c26

Observation c01a2a7a-cc13-4581-a16f-50370f7b4ba5 · outbound

This paper cites Exploring the limitations of behavior cloning for autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Exploring the limitations of behavior cloning for autonomous driving

Reference 13

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source=pdf_text observed=2026-08-11T18:16:00.370919Z digest=sha256:5069958d6c5860cd2db7180e996fa1fca020b12240a1c3fadfe8e22c2292aa24

Observation 736fa120-412c-4a35-ad4e-b3a7f0b6f42b · outbound

This paper cites Parting with Misconceptions about Learning-based Vehicle Motion Planning.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 14

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source=pdf_text observed=2026-08-11T18:16:00.375423Z digest=sha256:cb8ee692d77a8470383115a2e31186253b152084f67351bea9769d79c8439ca6

Observation b07fde82-4c29-46bc-af90-f9730ddaeb61 · outbound

This paper cites NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

Reference 15

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source=pdf_text observed=2026-08-11T18:16:00.380217Z digest=sha256:3ad2f372df9f79a5d5120de0493e2f30b612a8879ed11c20e42672c2293e2d31

Observation bb05725c-7583-40c1-bea7-8787c546b9ab · outbound

This paper cites Oasis: A universe in a transformer.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Oasis: A universe in a transformer

Reference 16

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source=pdf_text observed=2026-08-11T18:16:00.384480Z digest=sha256:2ef16ce882b9c0a06dcbef5d6a82f743543241fdc74fd0deb87177f9a7d65a94

Observation 2d28bc9c-e8ec-46f5-80b2-6927e77b4a97 · outbound

This paper cites Streetscapes: Large-scale Consistent Street View Generation Using Autoregressive Video Diffusion.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Streetscapes: Large-scale Consistent Street View Generation Using Autoregressive Video Diffusion

Reference 17

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T18:16:00.388314Z digest=sha256:86e279cd9b01dc69eaed3258a7777f3ecd310bc0e59bc649143b5349b057ec57

Observation 66dd9571-46e8-4bca-9a77-6465c3262d50 · outbound

This paper cites Carla: An open urban driv- ing simulator.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Carla: An open urban driv- ing simulator

Reference 18

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source=pdf_text observed=2026-08-11T18:16:00.392536Z digest=sha256:2058e9018f14374950102ca400ac5346deb8128bc994d453bc8f4e62f2ff86b8

Observation 5ddaeb27-c167-4967-b07d-fb5a2f4f6b82 · outbound

This paper cites FreeSim: Toward Free-viewpoint Camera Simulation in Driving Scenes.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model FreeSim: Toward Free-viewpoint Camera Simulation in Driving Scenes

Reference 19

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source=pdf_text observed=2026-08-11T18:16:00.396054Z digest=sha256:7447a75156ff25ad73b1e507523d5110ca6619c3f91e6643303accb98bc68764

Observation 0e0f4a2a-2982-4879-a5fc-9a16af1b5385 · outbound

This paper cites MagicDrive: Street View Generation with Diverse 3D Geometry Control.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model MagicDrive: Street View Generation with Diverse 3D Geometry Control

Reference 20

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source=pdf_text observed=2026-08-11T18:16:00.400036Z digest=sha256:b5f3cb1a86e6426b8805f19fec3db14716a73b6e27b0e208968db2b48801e8f5

Observation 0e9a7342-4812-4a36-819e-b84ad804dd6e · outbound

This paper cites Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 21

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source=pdf_text observed=2026-08-11T18:16:00.404849Z digest=sha256:b929df4e9ef4f9028f18de7758a21d0f38ef969cce37026b0f78324d32d46517

Observation cf1c8eb6-40cf-4a8d-a95d-c6b985804cea · outbound

This paper cites Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research

Reference 22

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source=pdf_text observed=2026-08-11T18:16:00.409469Z digest=sha256:abb76f479bd7d101ac7c3ae8c86bb5e21dfd4f0472485f26f8a4bf6122f1a1ec

Observation 9f938fba-0a46-4d42-89f4-3c3768121bc1 · outbound

This paper cites StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street Views.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street Views

Reference 23

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source=pdf_text observed=2026-08-11T18:16:00.414611Z digest=sha256:2e2b61b9f14a89187b23667447ba2f95abb175f0278449a43dbd184e32f57756

Observation c6903a7e-cf05-4a62-afa4-b2de682d8758 · outbound

This paper cites InfinityDrive: Breaking Time Limits in Driving World Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model InfinityDrive: Breaking Time Limits in Driving World Models

Reference 24

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source=pdf_text observed=2026-08-11T18:16:00.419693Z digest=sha256:8e491b2392430c913aee868ee92735f9671edddcd71a73092c39e0d1b5fdb3a7

Observation 159d322e-f718-49f5-aa94-3901dbc97c59 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 25

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source=pdf_text observed=2026-08-11T18:16:00.424590Z digest=sha256:94475446b23573084f0135750f2685b32d6152a474d7dabd73206d38d7da38c6

Observation e487f4d9-9295-4b2b-8a12-97ec4342c6a1 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Classifier-Free Diffusion Guidance

Reference 26

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source=pdf_text observed=2026-08-11T18:16:00.428476Z digest=sha256:9e290c3f918655b2cc72dcbb781b4b3b768e18537e677f1863e7be4ff541758a

Observation 8814aedd-4ef5-426a-a86d-28403be94202 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Denoising Diffusion Probabilistic Models

Reference 27

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source=pdf_text observed=2026-08-11T18:16:00.432716Z digest=sha256:b022489625f93b462a1c4f8a26cd968a6fffe41c43f11c472bf20582cf7eae95

Observation 3405a4ac-71d1-4a2e-818a-1cef4f5d709d · outbound

This paper cites Video Diffusion Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Video Diffusion Models

Reference 28

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source=pdf_text observed=2026-08-11T18:16:00.436622Z digest=sha256:401458573e24f28d39737b547808d063a862265cec541b4b175c7b869bec52c4

Observation fce77008-1c51-4d6c-aa34-7fd92ab2c201 · outbound

This paper cites Model-based imitation learn- ing for urban driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Model-based imitation learn- ing for urban driving

Reference 29

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source=pdf_text observed=2026-08-11T18:16:00.440603Z digest=sha256:eed62c261c446f396bf58028cd6926635c52648f22f61b64c687c78a3a67c448

Observation 129960d7-f4b7-4aee-881d-0151b131b475 · outbound

This paper cites GAIA-1: A Generative World Model for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model GAIA-1: A Generative World Model for Autonomous Driving

Reference 30

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source=pdf_text observed=2026-08-11T18:16:00.444500Z digest=sha256:36b73789d3bc1892959da25fe3c6d28c28bcf967f0f3f8874e5ad3c0e256dcb0

Observation deff79b3-55e3-40a2-975c-5d94c613d02b · outbound

This paper cites St-p3: End-to-end vision- based autonomous driving via spatial-temporal feature learning.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model St-p3: End-to-end vision- based autonomous driving via spatial-temporal feature learning

Reference 31

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source=pdf_text observed=2026-08-11T18:16:00.448771Z digest=sha256:6278a92ded646377388cf15c331031e48f43d3618f87a51ab1de85690e3bbd95

Observation c7b2b478-7124-4642-b951-fc32cb079ee9 · outbound

This paper cites Planning-oriented autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Planning-oriented autonomous driving

Reference 32

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source=pdf_text observed=2026-08-11T18:16:00.452505Z digest=sha256:6dfdae12801551229d9a374c12a5e256ff2fcf8441252fe2b0a6d8e6e54a0813

Observation dbef3310-e78f-4de8-977e-171e951b62d9 · outbound

This paper cites SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Control.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Control

Reference 33

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source=pdf_text observed=2026-08-11T18:16:00.456736Z digest=sha256:890a7726a6a5a0afcff666f54c8416390050b5ce238fa9c944e02469a1826c81

Observation 70a54b35-039d-4853-9eea-2895efec6872 · outbound

This paper cites $\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model $\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving

Reference 34

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source=pdf_text observed=2026-08-11T18:16:00.461456Z digest=sha256:9a6698b5cc5699143629b49027a367175e1debf4a0e6495da76523681c96e591

Observation 85244c64-28d6-487a-b5ae-79241fd8f837 · outbound

This paper cites NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes

Reference 35

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local_arxiv, observed 2026-08-11T18:16:01.822357Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T18:16:00.465877Z digest=sha256:f341bd812506df124ba25ec383e7d25fdb2870b6c92cd4048e87aed23525274e

Observation f84f5128-19fb-4265-8926-7994cdd6073d · outbound

This paper cites Hid- den biases of end-to-end driving models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Hid- den biases of end-to-end driving models

Reference 36

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source=pdf_text observed=2026-08-11T18:16:00.469885Z digest=sha256:97f0284f23c17379597fcf71caf71eac2b3e369a7310648b0ba94dca32d840f5

Observation 00d9b626-1e4d-4449-9856-4e6ae229054e · outbound

This paper cites ADriver-I: A General World Model for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model ADriver-I: A General World Model for Autonomous Driving

Reference 37

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source=pdf_text observed=2026-08-11T18:16:00.473564Z digest=sha256:60aebe5dec9ab5f69e017e44e815796ab5c862de507c0923887f120f5fc818c3

Observation b4a38aff-438a-45b2-b007-f5ffb8b2e570 · outbound

This paper cites Ide-net: Interactive driving event and pattern extrac- tion from human data.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Ide-net: Interactive driving event and pattern extrac- tion from human data

Reference 38

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source=pdf_text observed=2026-08-11T18:16:00.477598Z digest=sha256:e2c2c0859e880b96ec8490f1bc4f67f3f3af18d51b7637f70ad540600c70461a

Observation b8a30f18-7650-42bc-bff7-d92736cdd153 · outbound

This paper cites Multi-agent trajectory prediction by combining egocentric and allocentric views.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Multi-agent trajectory prediction by combining egocentric and allocentric views

Reference 39

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source=pdf_text observed=2026-08-11T18:16:00.481655Z digest=sha256:4416d3ab5856a07d150857fd2dc4adcae5bc65bec42dcb538aee1c4c838722ed

Observation e4c4861f-ca6c-4f10-8706-3dafd71d37a1 · outbound

This paper cites Towards capturing the tem- poral dynamics for trajectory prediction: a coarse-to-fine approach.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Towards capturing the tem- poral dynamics for trajectory prediction: a coarse-to-fine approach

Reference 40

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source=pdf_text observed=2026-08-11T18:16:00.485662Z digest=sha256:4f2d72cf474ed9210b61668ed8d2ffcb98662d241fada265691dd3567c147aa3

Observation e7a3af78-5f3e-4511-905f-825409e11854 · outbound

This paper cites Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding

Reference 41

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source=pdf_text observed=2026-08-11T18:16:00.489393Z digest=sha256:1608ca5217be4a79f0b66a64a609e0bc04eeff70878c93c5c94b9be322ba0006

Observation 844e3bed-28f6-4c64-b1fd-381732e9c210 · outbound

This paper cites Think twice be- fore driving: Towards scalable decoders for end-to-end au- tonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Think twice be- fore driving: Towards scalable decoders for end-to-end au- tonomous driving

Reference 42

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source=pdf_text observed=2026-08-11T18:16:00.493079Z digest=sha256:550bc1a312e3a1c7fbe99c7fedacefea9f8fb8d404d4f2e06fb9ec4c4f9356dd

Observation 485c95f1-ebae-4a5c-a5cb-20bc13765cf2 · outbound

This paper cites AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Driving

Reference 43

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source=pdf_text observed=2026-08-11T18:16:00.496640Z digest=sha256:57967215bcfc4fd55bae3bd28c35030f1a4881a4a79cef0393f0b55e8e14ebd4

Observation ee3f89b6-abfd-49e6-b779-30eecb97c3c9 · outbound

This paper cites Bench2drive: Towards multi-ability bench- marking of closed-loop end-to-end autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Bench2drive: Towards multi-ability bench- marking of closed-loop end-to-end autonomous driving

Reference 44

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source=pdf_text observed=2026-08-11T18:16:00.500331Z digest=sha256:682ac23e79a45ccf63d12d8d8fff67605728faaa697092add278d123040fde2d

Observation 18aff2cd-4d12-4f2d-b447-9cd35c3c9024 · outbound

This paper cites Vad: Vectorized scene repre- sentation for efficient autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Vad: Vectorized scene repre- sentation for efficient autonomous driving

Reference 45

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source=pdf_text observed=2026-08-11T18:16:00.504036Z digest=sha256:6df88d1581fb7966a76caf41d46eb41765bc9188def3a1e51343185ce9152043

Observation 88b880b2-07bb-4351-a0bc-e8cc628b4265 · outbound

This paper cites Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving

Reference 46

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source=pdf_text observed=2026-08-11T18:16:00.507758Z digest=sha256:cab177b1d4b601bbad6f7ead22601640c7cd8cc25cc231ae2f222744ace3a5f8

Observation cdc54a93-d814-495f-906a-11836f395cc1 · outbound

This paper cites an unresolved cited work.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Unresolved cited work

Reference 47

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source=pdf_text observed=2026-08-11T18:16:00.512547Z digest=sha256:e39ddd2ecf6101cb2ed236120145e9edf082f550cd9a60f67102f8c23ec999d9

Observation bcb8c85a-af38-4674-a1a1-50b9f516359f · outbound

This paper cites DriveGAN: Towards a Controllable High-Quality Neural Simulation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DriveGAN: Towards a Controllable High-Quality Neural Simulation

Reference 48

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source=pdf_text observed=2026-08-11T18:16:00.516284Z digest=sha256:c757759c18ad1d38f0d35bf18a6ef2a7eb5f323bfc8ebdedc5804b3e5f9e2df6

Observation 83f78938-b6f4-4685-a5c0-4230f743d06e · outbound

This paper cites Professor forcing: A new algorithm for training recurrent networks.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Professor forcing: A new algorithm for training recurrent networks

Reference 49

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source=pdf_text observed=2026-08-11T18:16:00.520381Z digest=sha256:003543da7f0978a855a090db943fb4f72b16d8a2b6c75528d7a82fa96556556c

Observation 38fec6af-989b-4869-b4cd-58f62144e912 · outbound

This paper cites Delving into the devils of bird’s-eye- view perception: A review, evaluation and recipe.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Delving into the devils of bird’s-eye- view perception: A review, evaluation and recipe

Reference 50

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source=pdf_text observed=2026-08-11T18:16:00.524256Z digest=sha256:213477fe85e44b2c2b90317579a7ac9278dedb792519c767c4aaa3505486a43b

Observation 80975db4-547b-4a7e-81ae-1fabcf1ea644 · outbound

This paper cites Think2drive: Efficient reinforcement learning by thinking in latent world model for quasi-realistic autonomous driv- ing (in carla-v2).

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Think2drive: Efficient reinforcement learning by thinking in latent world model for quasi-realistic autonomous driv- ing (in carla-v2)

Reference 51

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source=pdf_text observed=2026-08-11T18:16:00.527977Z digest=sha256:d8152343ceee4044fef5fcbc78a95de34d21a15a483b26f4735f26d3d58cba4a

Observation eb4d67a0-2ec1-4a0a-bfc5-8be30722c115 · outbound

This paper cites DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

Reference 52

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source=pdf_text observed=2026-08-11T18:16:00.531625Z digest=sha256:721c42e452fe0434282d325ac86c98ca01ef9b53c1a751b56de2454f81afafc7

Observation 6d8bc2b3-ed61-4b8c-8595-596b44504983 · outbound

This paper cites GLIGEN: Open-Set Grounded Text-to-Image Generation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model GLIGEN: Open-Set Grounded Text-to-Image Generation

Reference 53

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source=pdf_text observed=2026-08-11T18:16:00.535988Z digest=sha256:bf04708779d313f591e6f10aa0bf43050cbfdc3cb83e1df61c07dd9e99f6aad7

Observation 198247ee-6bce-42aa-9699-661f1cbcee4c · outbound

This paper cites Enhancing End-to-End Autonomous Driving with Latent World Model.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Enhancing End-to-End Autonomous Driving with Latent World Model

Reference 54

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source=pdf_text observed=2026-08-11T18:16:00.540418Z digest=sha256:16c9481a812ffaf06a7fa4b0b5d2195604b9b4b45bd665fda6b5936fc483fed4

Observation a4bd2a96-ee64-4291-af1f-559ed707b457 · outbound

This paper cites BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Reference 55

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T18:16:00.545200Z digest=sha256:45dbd5f1e0e889a37893de3647a5731a74f66e5fa30849c70f458ff24784ba3d

Observation a70a4d95-1e5e-4a85-a778-d1eb20ef1107 · outbound

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

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 56

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source=pdf_text observed=2026-08-11T18:16:00.549696Z digest=sha256:59fa25651306ee71a9aac6f8a130e02ddbd023b726708d56db575ea4ef55bb04

Observation 5a86e787-1096-48ff-8718-8790d6b54a3b · outbound

This paper cites Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?

Reference 57

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source=pdf_text observed=2026-08-11T18:16:00.554168Z digest=sha256:4d8f82fbd5f00d33585ece2c453f2c4e48ad2879b32a99008cf7365f356b429d

Observation 9b3bd9e7-ebc6-4c5d-92e5-31f37883ce1f · outbound

This paper cites LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching

Reference 58

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source=pdf_text observed=2026-08-11T18:16:00.559193Z digest=sha256:e2afbc69e74251e3fab6105b5e9a202b63d734aa6471a94d8378ff2352010755

Observation 568de074-21e3-400e-b558-03bfb3fcb6f1 · outbound

This paper cites PETR: Position Embedding Transformation for Multi-View 3D Object Detection.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model PETR: Position Embedding Transformation for Multi-View 3D Object Detection

Reference 59

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source=pdf_text observed=2026-08-11T18:16:00.563583Z digest=sha256:9f9102e5dd61232cb3d1d6240c6c3ed38dd03567f612c0e7cb09fd2119cf2faa

Observation c51fea18-95a8-4941-8152-f9a8ce6326de · outbound

This paper cites PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

Reference 60

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source=pdf_text observed=2026-08-11T18:16:00.567802Z digest=sha256:2dde3debecf1651f0070a5453b3fa291d4be7e276ddabc23cd23e895f0550afe

Observation 609b1133-50f4-47ac-8722-00eff3d0c543 · outbound

This paper cites BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

Reference 61

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source=pdf_text observed=2026-08-11T18:16:00.572098Z digest=sha256:abbc586004e8c0f469d71313b244673d30ae24262ca457bd4b9c4106a2256482

Observation 2498d6aa-68a9-416f-b788-7afad5cd419c · outbound

This paper cites Urban Radiance Field Representation with Deformable Neural Mesh Primitives.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Urban Radiance Field Representation with Deformable Neural Mesh Primitives

Reference 62

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verified exact
local_arxiv, observed 2026-08-11T18:16:01.594370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T18:16:00.576201Z digest=sha256:c883bd8d950cee36835a362ca9ba42ce850279a39497364aeb7504c36f5bd5dc

Observation 4c8b09cf-c999-4398-8b0c-4dc8980a2c10 · outbound

This paper cites ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving

Reference 63

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source=pdf_text observed=2026-08-11T18:16:00.580280Z digest=sha256:ab39d110897532c1e1f2eaae3609981617d787a7edace567c52230563378c6a9

Observation d8280352-6cf7-45bd-9840-a70c6466288d · outbound

This paper cites InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models

Reference 64

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source=pdf_text observed=2026-08-11T18:16:00.583928Z digest=sha256:8ab00687cd207fa4d5536a6fba59415f76a798db8fcf07ef65b3aa127947bfba

Observation 915929db-24fc-4c26-845c-d050adce873e · outbound

This paper cites Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generation

Reference 65

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source=pdf_text observed=2026-08-11T18:16:00.587622Z digest=sha256:694b413fd68d67993510025f021593d870dc8b71b60143e3da91735bffa4b8e5

Observation 8e9dfdf0-1c94-463d-9284-8908d6842845 · outbound

This paper cites T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

Reference 66

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source=pdf_text observed=2026-08-11T18:16:00.591641Z digest=sha256:c41c8d0ec552edb6e7ac138818e766acae2f12f2c0c3b7c7a834416acf2bd626

Observation f1a44506-0111-4310-8b8e-592f575b8463 · outbound

This paper cites ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration

Reference 67

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source=pdf_text observed=2026-08-11T18:16:00.595485Z digest=sha256:34e3b30bdde668124ab2de5b15b98a9f33c2431a8971f111e1c0e4ca3b4ce8fe

Observation 1a5608bc-2e53-41f6-947b-a5ed0c359762 · outbound

This paper cites Alvinn: An autonomous land vehicle in a neural network.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Alvinn: An autonomous land vehicle in a neural network

Reference 68

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source=pdf_text observed=2026-08-11T18:16:00.601593Z digest=sha256:81b62c166cbeb71cea88e3e2a384b7ca9987e738c213f2ae12a8034d9d1de156

Observation 8f925db0-331c-4dd9-9bb1-3cddd77de90b · outbound

This paper cites Multi-modal fusion transformer for end-to-end autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Multi-modal fusion transformer for end-to-end autonomous driving

Reference 69

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source=pdf_text observed=2026-08-11T18:16:00.608276Z digest=sha256:429ff528118db5b621bc771ebd80a68328c7a1463891e4376a0ddd7618525c12

Observation ce087c68-4e46-4611-a0de-d4187995771a · outbound

This paper cites Urban Radiance Fields.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Urban Radiance Fields

Reference 70

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source=pdf_text observed=2026-08-11T18:16:00.612375Z digest=sha256:8dc992fbbe65fe2627303e5ce52592a320634a8760cde00715e5fc242bee0727

Observation 69af8bc4-cbdb-49d1-9135-ac9121e32550 · outbound

This paper cites Sophia Koepke, Zeynep Akata, and Andreas Geiger.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Sophia Koepke, Zeynep Akata, and Andreas Geiger

Reference 71

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Observation 8d76a8ce-e94e-46e0-91bd-82780b4ad712 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model High-resolution image synthesis with latent diffusion models

Reference 72

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source=pdf_text observed=2026-08-11T18:16:00.621528Z digest=sha256:29445a66b22ded7ad3ab48200d89d747be6b31ac9bb090b2b3621ba22d7f5558

Observation 85d18a89-abd1-41b1-976d-cb2600cfd70a · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model High-Resolution Image Synthesis with Latent Diffusion Models

Reference 73

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Observation f2b0f04d-a53b-4124-b8c8-979f94dcde9e · outbound

This paper cites Efficient reductions for imitation learning.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Efficient reductions for imitation learning

Reference 74

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source=pdf_text observed=2026-08-11T18:16:00.630414Z digest=sha256:ea2566333242963fd4d743340f60ad428aba4e4e8c39fa2efd5c03b706934e7c

Observation dd45a3ac-09e6-4bf6-90ca-03a29c0011de · outbound

This paper cites Safety-enhanced autonomous driving using in- terpretable sensor fusion transformer.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Safety-enhanced autonomous driving using in- terpretable sensor fusion transformer

Reference 75

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source=pdf_text observed=2026-08-11T18:16:00.634248Z digest=sha256:c40fd821841755b37bd8295f3b4f0ca47f120898ca9d2b5ad820c61d7259430c

Observation 56cd1548-6282-4a04-9f96-c8bd5e3e93d7 · outbound

This paper cites Reasonnet: End-to-end driving with temporal and global reasoning.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Reasonnet: End-to-end driving with temporal and global reasoning

Reference 76

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source=pdf_text observed=2026-08-11T18:16:00.638230Z digest=sha256:c0a372cc0cf14ea73edc8f1072ffaa895f79c0970b7b377095e22c2fb01ea5ed

Observation 946888dc-9f7e-4c86-b356-18cbb7ae6e89 · outbound

This paper cites Denoising Diffusion Implicit Models.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Denoising Diffusion Implicit Models

Reference 77

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source=pdf_text observed=2026-08-11T18:16:00.642482Z digest=sha256:024c8e9bda72975db34b7da510a98703fc90d612470b8e6abcd0e9f536e9872d

Observation 2392ad15-5163-4376-ac20-62a6e3cfc202 · outbound

This paper cites Difsd: Ego-centric fully sparse paradigm with uncertainty denoising and iter- ative refinement for efficient end-to-end autonomous driv- ing.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Difsd: Ego-centric fully sparse paradigm with uncertainty denoising and iter- ative refinement for efficient end-to-end autonomous driv- ing

Reference 78

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source=pdf_text observed=2026-08-11T18:16:00.646661Z digest=sha256:be5ca69e49e14ecbf66f924814cc8699f91457656c0d8759a4cbd6c5e8f219c4

Observation 44be76ab-196d-4017-ab00-48567ab3f959 · outbound

This paper cites SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation

Reference 79

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source=pdf_text observed=2026-08-11T18:16:00.651323Z digest=sha256:2685a5c682d8936d0b47d2e4df6f1dce97fde29c99298ac7938db680a25d565c

Observation 2ee22585-1ccf-4b2d-8bcf-d559d21d0d28 · outbound

This paper cites Street-View Image Generation from a Bird's-Eye View Layout.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Street-View Image Generation from a Bird's-Eye View Layout

Reference 80

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source=pdf_text observed=2026-08-11T18:16:00.655334Z digest=sha256:6b4f1cbf87a61c57c7a14af69bdd7d7412867cbdbec4984eede91f785d1cfdf5

Observation 025b101e-097b-4f35-914b-90d20daddea1 · outbound

This paper cites Block-NeRF: Scalable Large Scene Neural View Synthesis.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Block-NeRF: Scalable Large Scene Neural View Synthesis

Reference 81

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source=pdf_text observed=2026-08-11T18:16:00.659828Z digest=sha256:08ece4838f398ca7822cd41e84a662a93b7b3cf083fc7befbcf09327f30a8cdc

Observation d29e0eb1-d5a5-43d4-a387-78822e074116 · outbound

This paper cites DrivingForward: Feed-forward 3D Gaussian Splatting for Driving Scene Reconstruction from Flexible Surround-view Input.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DrivingForward: Feed-forward 3D Gaussian Splatting for Driving Scene Reconstruction from Flexible Surround-view Input

Reference 82

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source=pdf_text observed=2026-08-11T18:16:00.663808Z digest=sha256:a6df198ec95fd4b740120758e6b3dc0753904694e93079b73431892cd98bc137

Observation 55a60a8d-f6b2-4156-b533-bfd4f8b04838 · outbound

This paper cites Con- gested traffic states in empirical observations and micro- scopic simulations.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Con- gested traffic states in empirical observations and micro- scopic simulations

Reference 83

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source=pdf_text observed=2026-08-11T18:16:00.668740Z digest=sha256:494289c0ef26045002ef3d948b4696e8d8a1ab64799589c84c25a747dcbaac0e

Observation bf9c3065-ad41-45ec-b5a4-3b3eb1b41408 · outbound

This paper cites Diffusion Models Are Real-Time Game Engines.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Diffusion Models Are Real-Time Game Engines

Reference 84

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source=pdf_text observed=2026-08-11T18:16:00.672957Z digest=sha256:4abed8e76158794ccf83ae1322e67ab839bb40130601a73cfe6fe900fe267d56

Observation 97ef0fb0-cd67-484e-842c-14b751ba3eff · outbound

This paper cites FreeVS: Generative View Synthesis on Free Driving Trajectory.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model FreeVS: Generative View Synthesis on Free Driving Trajectory

Reference 85

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source=pdf_text observed=2026-08-11T18:16:00.676984Z digest=sha256:baac83cf4f449300fda6f2458230a825670857b607cd22eec9ea2d3cb9bf6d4d

Observation f0b927c7-0c02-4d9b-8a8c-10b03cf7ddf5 · outbound

This paper cites Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

Reference 86

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source=pdf_text observed=2026-08-11T18:16:00.681081Z digest=sha256:dbd564efbea1f89a2ffbdac5d3fd52be9adf909e2a6eeb13ac127753ffb43cb0

Observation e03c1fdf-6393-4f86-8a78-12aa14e49884 · outbound

This paper cites DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

Reference 87

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source=pdf_text observed=2026-08-11T18:16:00.685277Z digest=sha256:fab112d10444b85aed76c082275eea96b06337d5e4f80458f65325d1966629d3

Observation 8689e171-6ffd-4bd5-8315-cf8a6d575c1f · outbound

This paper cites Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving

Reference 88

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source=pdf_text observed=2026-08-11T18:16:00.689153Z digest=sha256:eec49075ce4c3c5fe750bbfdc8e121e09e5dea198bef213ecd19a7c6a253a903

Observation 247fcb98-d204-4dcc-b45b-29bbce645f24 · outbound

This paper cites Panacea: Panoramic and Controllable Video Generation for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Panacea: Panoramic and Controllable Video Generation for Autonomous Driving

Reference 89

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source=pdf_text observed=2026-08-11T18:16:00.692815Z digest=sha256:e623d0a09a589a9ac2143dbc638701ee2c1bf9cddd9a7ceaffe398ffa1f52355

Observation c2737a3d-d865-4273-91d3-fb5df3d4dd3f · outbound

This paper cites Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving

Reference 90

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source=pdf_text observed=2026-08-11T18:16:00.696503Z digest=sha256:885e1782b8008a977e9735221405bd532da3f733bb562582a89ca6f5e4bdf5f5

Observation b5d9ee3e-bc05-4974-ab8d-1e4ff12252a2 · outbound

This paper cites Para-drive: Parallelized architecture for real-time autonomous driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Para-drive: Parallelized architecture for real-time autonomous driving

Reference 91

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source=pdf_text observed=2026-08-11T18:16:00.701155Z digest=sha256:bc10fadd9d1f8bc0096831f995f18f36a6671b7405773ce09c33da0ebcb41a90

Observation 4c197b00-9bfa-4794-af9a-485128ae90c4 · outbound

This paper cites Trajectory-guided control pre- diction for end-to-end autonomous driving: A simple yet strong baseline.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Trajectory-guided control pre- diction for end-to-end autonomous driving: A simple yet strong baseline

Reference 92

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source=pdf_text observed=2026-08-11T18:16:00.705617Z digest=sha256:797dfe86b9f6f71cbc7f9cfe6244a9155fe45ceb3030643067e0e0cc86ba79a5

Observation e6bb3681-4f3f-44b8-8297-af5a21a1795e · outbound

This paper cites Policy pre-training for autonomous driv- ing via self-supervised geometric modeling.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Policy pre-training for autonomous driv- ing via self-supervised geometric modeling

Reference 93

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source=pdf_text observed=2026-08-11T18:16:00.710187Z digest=sha256:45308459b3f505cf28ab1379cc854ba93c61e533f95da2c7bdbb386f40b20d5e

Observation e28ab126-1ebc-482a-92c8-4be8ea422582 · outbound

This paper cites DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation

Reference 95

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source=pdf_text observed=2026-08-11T18:16:00.719113Z digest=sha256:0f3aeb7ec8a9120cd720ad93e961bad184b7e90850fa4c9edb83ec9591fb1d44

Observation e64c3edc-81c2-4a5d-999f-caa0beaaa2d4 · outbound

This paper cites BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

Reference 96

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source=pdf_text observed=2026-08-11T18:16:00.724016Z digest=sha256:02d7301e56665fa62bdfdc15637476c5f22e94fdbfd4c71285fd39a6d4885bc2

Observation d7a77413-0ae2-4103-8a37-36b4b0382a45 · outbound

This paper cites DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation

Reference 97

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source=pdf_text observed=2026-08-11T18:16:00.728435Z digest=sha256:e7ada71d5a3b879b4787c55f45ccb428ce6dcb44e1a9f1cd43bc0b8546851a43

Observation 3f0245c7-4fd7-4fb9-b3d3-87e8d22cde02 · outbound

This paper cites Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

Reference 98

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source=pdf_text observed=2026-08-11T18:16:00.732842Z digest=sha256:6a8ef2a6da3c2a8ea118dd4577b5dbf4dce91a5925d3c4c92084f5cffeaa1ffc

Observation eb8e99d8-7127-4310-ac80-d51f466c3142 · outbound

This paper cites BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout

Reference 99

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source=pdf_text observed=2026-08-11T18:16:00.737937Z digest=sha256:44a6a964712a29411fac57a542d48d22c3d41355c44f667ba813cb886c1ea470

Observation bf31aba8-3c48-4cc5-a8fb-7c9168469214 · outbound

This paper cites DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving

Reference 100

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source=pdf_text observed=2026-08-11T18:16:00.742072Z digest=sha256:d0aa9607de169bc6c77ecd5505e3d0fd0bd899a6a35f79174ffc2b52875176c7

Observation a5b2bc3c-b5f4-4209-b58f-b942e124ddb9 · outbound

This paper cites UniSim: A Neural Closed-Loop Sensor Simulator.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model UniSim: A Neural Closed-Loop Sensor Simulator

Reference 101

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verified exact
local_arxiv, observed 2026-08-11T18:16:01.094088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T18:16:00.746423Z digest=sha256:36545faa970f831503166e80cbf7ac2845f146d9c8c48de55f913a01afdb831b

Pith citing papers

Observation 95572721-5ba4-4f16-9a7f-40715e497627 · inbound

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving cites this paper.

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 12

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arxiv_id, observed 2026-05-22T14:31:40.609301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-22T14:30:47.787654Z digest=sha256:e41bbd12b96169bab7d41296cdb35ff01e5b923c4847c3ed402c94ce5eb1a05a

Observation bae4d0cf-1770-4a61-a723-31a3cea27b8b · inbound

DriveCamSim: Generalizable Camera Simulation via Explicit Camera Modeling for Autonomous Driving cites this paper.

DriveCamSim: Generalizable Camera Simulation via Explicit Camera Modeling for Autonomous Driving Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 27

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source=pdf_text observed=2026-08-07T14:12:11.217599Z digest=sha256:1aafd5db8ff3a5f4d024ac3686ae656286aacec9ccc830c1f293880c2de5ef65

Observation e8d03209-6a12-4569-8281-321abf54c392 · inbound

ReSim: Reliable World Simulation for Autonomous Driving cites this paper.

ReSim: Reliable World Simulation for Autonomous Driving Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 95

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arxiv_id, observed 2026-05-19T09:32:16.707413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-19T09:28:00.597160Z digest=sha256:44165dd87a1b8b25f03be5ac84f39c4a0a09cbabe561a84a141bcc03e5ea5688

Observation 69309f5c-bedf-4445-93f1-3b5a7e5ee33a · inbound

SimScale: Learning to Drive via Real-World Simulation at Scale cites this paper.

SimScale: Learning to Drive via Real-World Simulation at Scale Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 84

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arxiv_id, observed 2026-05-17T04:34:01.818312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-17T04:33:03.629533Z digest=sha256:52a9b11333e2b41c039d04bf6f1f9ae8631f9a62b91048a29a2dcbbb59fd40c7

Observation ef91c466-53dc-4222-9e4f-a5d35d105879 · inbound

Sim2Real-AD: A Modular Sim-to-Real Framework for Deploying VLM-Guided Reinforcement Learning in Real-World Autonomous Driving cites this paper.

Sim2Real-AD: A Modular Sim-to-Real Framework for Deploying VLM-Guided Reinforcement Learning in Real-World Autonomous Driving Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 16

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metadata mismatch
arxiv_id, observed 2026-05-13T18:23:06.428157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T18:19:05.977682Z digest=sha256:1565dbe4f62bb1ae95a9314848bd8013fec1cfcfc2dc64f376e25563854c8544

Observation 3d818f2f-3851-4035-9732-52f6c08411ed · inbound

Dreaming Across Towns: Semantic Rollout and Town-Adversarial Regularization for Zero-Shot Held-Out-Town Fixed-Route Driving in CARLA cites this paper.

Dreaming Across Towns: Semantic Rollout and Town-Adversarial Regularization for Zero-Shot Held-Out-Town Fixed-Route Driving in CARLA Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:36:30.792602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-07T05:15:23.174640Z digest=sha256:cb6713495786066c0b0e9d14470746317660c4654316166e5cde8f68c7e5b222

Observation 3f8fdc78-6a53-4690-9db4-141719731997 · inbound

Agent-driven Long-tail Simulation for Autonomous Driving cites this paper.

Agent-driven Long-tail Simulation for Autonomous Driving Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-11T20:01:39.628512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T20:01:39.628512Z digest=sha256:f65a5dd0b802415cd8fcd14d4b69edaf8135d6c0d673b0a755ffbe8bbbedcd7d

Observation d09263c3-f043-4692-bee3-7ad36bf92fd3 · inbound

Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation cites this paper.

Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-07-08T03:24:28.720022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-08T03:20:39.917042Z digest=sha256:2a82297da0f345b642a8a6e9654340e7e70316e7871ea3b090f02eb7e5654c8a