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Paper Citation Record · LEDGER

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

As of 7 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 29 inbound Pith citation observations for arXiv:2505.23757.

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

pith.paper-citation-record.v1
2505.23757 v1

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:43:58.997932Z

measured 116 of 116 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:31:04.384791Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T08:36:59.862431Z

Reference resolution

87 of 87 outbound references displayed

  • verified exact2
  • verified fuzzy26
  • unresolved58
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a10d2d51-7056-40df-85db-bffb9279fc94 · outbound

This paper cites GPT-4 Technical Report.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-07T12:43:52.448551Z digest=sha256:008d1829f64a5b5e519abfafef210d7040093ba0ec70d1f151ef075e530f5948

Observation 0e1a8d2b-7c83-4323-af40-283c5fcaa33a · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

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source=pdf_text observed=2026-08-07T12:43:52.550258Z digest=sha256:593fcf5dc109ea289d614e3e07b1dba0e975fb2019eedbdf66bdba86d976f25c

Observation b502bf3b-0a0d-41e8-991d-08adcc1c2fd2 · outbound

This paper cites Qwen2.5-VL Technical Report.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Qwen2.5-VL Technical Report

Reference 4

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source=pdf_text observed=2026-08-07T12:43:52.772359Z digest=sha256:b772860d14bfef2b4eab76dd9c57dfabe045b9a111499ba14509d67c77e4f66f

Observation 7bbad7fa-4c5a-4587-b967-7465c9bdef93 · outbound

This paper cites Fishyscapes: A benchmark for safe semantic segmentation in autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Fishyscapes: A benchmark for safe semantic segmentation in autonomous driving

Reference 5

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source=pdf_text observed=2026-08-07T12:43:52.884004Z digest=sha256:e96c35dbe631b83b8ee096e8a98e7dbdefd9b88b4c7c90625c5c8e32b2b3e11e

Observation 80a78b90-59ec-43a0-9dad-eb2e8c3343ca · outbound

This paper cites UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving

Reference 6

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source=pdf_text observed=2026-08-07T12:43:53.034369Z digest=sha256:9f7bd45087e5e139d0a435e7dc8808fd26858889614e55464dc5eeafd6ec432a

Observation d1ce83ed-dc78-4220-999f-e1b49e987b28 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models nuscenes: A multimodal dataset for autonomous driving

Reference 7

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source=pdf_text observed=2026-08-07T12:43:53.121418Z digest=sha256:6b0a38f6a7e05f0f15a921c27b6cac7b934a36a5c71e962110df49e8974298f8

Observation 26736415-571b-4adb-a88b-48c0ee75a23c · outbound

This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 8

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source=pdf_text observed=2026-08-07T12:43:53.171614Z digest=sha256:3030c3588c68e1bf8eef1e84e5b7d8e3484dcf6525d3fe7c9b0390a3108018a2

Observation 24317afe-9fc7-40a7-b2d5-22bac49689db · outbound

This paper cites Argoverse: 3d tracking and forecasting with rich maps.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Argoverse: 3d tracking and forecasting with rich maps

Reference 9

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source=pdf_text observed=2026-08-07T12:43:53.235636Z digest=sha256:8f0f9a0d86a22c0984948f9fd50143b961ba818c4bcf740e79f350ab3343219c

Observation 3208e4ff-2c46-43c4-98ee-3ba3029e6d94 · outbound

This paper cites Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving

Reference 10

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source=pdf_text observed=2026-08-07T12:43:53.357114Z digest=sha256:0bc896a1f61c84129877b9508a2e68f0a695f1402560a4668caaa7e9b882b246

Observation 212a2b96-5d96-445c-8edd-38255f37563b · outbound

This paper cites VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

Reference 11

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source=pdf_text observed=2026-08-07T12:43:53.449636Z digest=sha256:34b26180f392d0dc2f43807f8ab2a1880fa117147c78d5ce61c8c48713abbafb

Observation 2a60960a-d589-4686-b944-501628b7dc39 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 12

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source=pdf_text observed=2026-08-07T12:43:53.498716Z digest=sha256:20b5e17e95134d53de088be4dfd5e15e3f21e596c139f025a22563f087ce501a

Observation 63e28846-2f63-4b4d-abfa-16f5b69a3f7b · outbound

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

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Exploring the limitations of behavior cloning for autonomous driving

Reference 13

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source=pdf_text observed=2026-08-07T12:43:53.560050Z digest=sha256:ceb366e4ac179133d50dde974d3cad3247c1ff971a94bee6dbba7ed92e4b8abb

Observation 1350197a-208c-452c-a0ee-40388fa8fc18 · outbound

This paper cites Navsim: Data-driven non- reactive autonomous vehicle simulation and benchmarking.Advances in Neural Information Processing Systems, 37:28706–28719, 2024.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Navsim: Data-driven non- reactive autonomous vehicle simulation and benchmarking.Advances in Neural Information Processing Systems, 37:28706–28719, 2024

Reference 14

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source=pdf_text observed=2026-08-07T12:43:53.653787Z digest=sha256:1b9fadcce114aa883c8a716ba9e397ba19e12ffc58f0dc254c49641d8fd610bf

Observation d295e31f-64dc-42ab-bb2a-e584f48cca0c · outbound

This paper cites Talk2Car: Taking Control of Your Self-Driving Car.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Talk2Car: Taking Control of Your Self-Driving Car

Reference 15

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source=pdf_text observed=2026-08-07T12:43:53.696335Z digest=sha256:174c9eb563e0ae8eb7f568c7fcece2f334984f04d8710a2d12083cfeb8fdae45

Observation 0759dfdb-5a24-45cb-83f9-8a88413ea2f3 · outbound

This paper cites Pixel-wise anomaly detection in complex driving scenes.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Pixel-wise anomaly detection in complex driving scenes

Reference 16

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source=pdf_text observed=2026-08-07T12:43:53.721481Z digest=sha256:8be1b68e78d872ded85c0e6ce065ec7fc1ebaf3b330dbcf1f8c5a01ffbb1a01c

Observation aa9b24ba-3d67-4b4b-ab1b-951511837eed · outbound

This paper cites Hint-AD: Holistically Aligned Interpretability in End-to-End Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Hint-AD: Holistically Aligned Interpretability in End-to-End Autonomous Driving

Reference 17

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source=pdf_text observed=2026-08-07T12:43:53.752395Z digest=sha256:bc84539c6f2736d2a6636664a752ccaf52836a419fa6a59c955cf89fdff94dd0

Observation 63aef99d-c6b4-45a9-88a0-8d37a5329bda · outbound

This paper cites Idd-3d: Indian driving dataset for 3d unstructured road scenes.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Idd-3d: Indian driving dataset for 3d unstructured road scenes

Reference 18

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source=pdf_text observed=2026-08-07T12:43:53.830196Z digest=sha256:6bf2ce80617ef07af85437173e54f502ef60f0b61181eda621560ce79932c2e8

Observation 76d49308-e499-476f-a0a7-f6ea89406f18 · outbound

This paper cites Carla: An open urban driving simulator.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Carla: An open urban driving simulator

Reference 19

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source=pdf_text observed=2026-08-07T12:43:53.895816Z digest=sha256:8163e81c493b10c67fcd59702cbf655056fe386d093be0b1d609920919cf039b

Observation 93aea4b8-0a05-4728-b8ae-2daddcb8919f · outbound

This paper cites Scp- diff: Spatial-categorical joint prior for diffusion based semantic image synthesis.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Scp- diff: Spatial-categorical joint prior for diffusion based semantic image synthesis

Reference 20

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source=pdf_text observed=2026-08-07T12:43:53.949655Z digest=sha256:84aaea5720f0171a733d0a88d7d45247cbb106ba3c74e6d1a87e32e1dae411e6

Observation afc9e56e-04ce-49ed-972b-56964b82372b · outbound

This paper cites Vision meets robotics: The kitti dataset.The international journal of robotics research, 32(11):1231–1237, 2013.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Vision meets robotics: The kitti dataset.The international journal of robotics research, 32(11):1231–1237, 2013

Reference 21

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source=pdf_text observed=2026-08-07T12:43:54.073828Z digest=sha256:ad13d2caa6fbb165484e431ca6dc19e21a70d9e493d33b03d9d2c500a9958f1b

Observation d96b76f2-f3a2-4d7c-8b9a-bacc479beac4 · outbound

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

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning

Reference 22

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source=pdf_text observed=2026-08-07T12:43:54.163868Z digest=sha256:5a282f3d59c5984600013550b6d173aff2ce1393710adf397fd014f7a426a61c

Observation 73d29622-2013-47dd-9ff6-7c26a05aea5b · outbound

This paper cites Planning-oriented autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Planning-oriented autonomous driving

Reference 23

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source=pdf_text observed=2026-08-07T12:43:54.308023Z digest=sha256:5890596bf47e7355715009d3a8b5bba341409d84f6eb8d31d48c85c7ccd3856b

Observation 29ed6ffb-3f55-4935-8502-a113f19e44b6 · outbound

This paper cites GPT-4o System Card.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models GPT-4o System Card

Reference 24

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source=pdf_text observed=2026-08-07T12:43:54.581479Z digest=sha256:a4b58b9cf27c1cff9d2a554e1199bcb6627a7b8de5d01c1b7500d1dccc2494cf

Observation 9746c94c-552a-4f6f-a3cf-e51c4af7cde6 · outbound

This paper cites EMMA: End-to-End Multimodal Model for Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models EMMA: End-to-End Multimodal Model for Autonomous Driving

Reference 25

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source=pdf_text observed=2026-08-07T12:43:54.713487Z digest=sha256:cf7e46036cc3938ef16841100537628e954d8fa395bf011fd6fedeb2d53ad221

Observation 61f869b5-bc0a-48bf-95f8-9d73ada5e3a0 · outbound

This paper cites Driveadapter: Breaking the coupling barrier of perception and planning in end-to-end au- tonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Driveadapter: Breaking the coupling barrier of perception and planning in end-to-end au- tonomous driving

Reference 26

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source=pdf_text observed=2026-08-07T12:43:54.988387Z digest=sha256:e0cea844d67615e4f8293e1d221aab3427085e684ea036483dd983d84236e3a0

Observation 6b2882a8-35d7-433d-9b7b-e2f18872a0c0 · outbound

This paper cites Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving

Reference 27

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source=pdf_text observed=2026-08-07T12:43:55.071281Z digest=sha256:21ff2cb4585f2c0b5cebdba82319fef35b06b1493560d0b19c7a8d8b6c4b651d

Observation c0930aff-f9ef-424a-b145-d4c73b2cdbb8 · outbound

This paper cites Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving

Reference 28

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source=pdf_text observed=2026-08-07T12:43:55.159426Z digest=sha256:d71104e875f092729556190456c0ef419040ef3f46cefa02928bcf88970e09a8

Observation b9183ddc-f8f5-41e7-b2cd-44a86d43be99 · outbound

This paper cites Vad: Vectorized scene representation for efficient autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Vad: Vectorized scene representation for efficient autonomous driving

Reference 29

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source=pdf_text observed=2026-08-07T12:43:55.204126Z digest=sha256:ebaa6977b4d7c41c1a631d602e9800f5ff7317e36ed232c6a1fb3dd064574f35

Observation 23f3dfe6-0b3b-40b5-8fa2-5a41c99b67e9 · outbound

This paper cites P-mapnet: Far-seeing map generator enhanced by both sdmap and hdmap priors.IEEE Robotics and Automation Letters, 2024.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models P-mapnet: Far-seeing map generator enhanced by both sdmap and hdmap priors.IEEE Robotics and Automation Letters, 2024

Reference 30

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:55.252353Z digest=sha256:bb191bbfb14ac69abd90a07a734bc965d9ec2682d8377fa06f69e082304ab97d

Observation f801b714-02da-4f08-a8cb-e5fe5dec14ba · outbound

This paper cites Adapt: Action-aware driving caption transformer.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Adapt: Action-aware driving caption transformer

Reference 31

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:55.289844Z digest=sha256:55112e0ef4c6faab738f88537e72d05db1cf68e014d5993da7b64dae93155859

Observation c2977a51-0889-45fc-9f9a-eec082c71f38 · outbound

This paper cites Tod3cap: Towards 3d dense captioning in outdoor scenes.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Tod3cap: Towards 3d dense captioning in outdoor scenes

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:55.393975Z digest=sha256:f9a59881f99b4b3649500495a05e79b5cabe8dd8ac598a9f02e092d1cafbd9ba

Observation f7453340-93d8-47f1-a77c-e2ff434849d1 · outbound

This paper cites Textual explana- tions for self-driving vehicles.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Textual explana- tions for self-driving vehicles

Reference 33

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:55.528628Z digest=sha256:67cff340168aada8dcdee36b22955765288ed73b09721ead9aa890666012c9bb

Observation 96e917c7-891a-4741-a3a0-f65f89451a23 · outbound

This paper cites UniScene: Unified Occupancy-centric Driving Scene Generation.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models UniScene: Unified Occupancy-centric Driving Scene Generation

Reference 34

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source=pdf_text observed=2026-08-07T12:43:55.666234Z digest=sha256:f611c414c236607306547b36e7e18ff83e0d2e4ab1aa4660aeeae8d2f412e432

Observation 9e33c1fd-63ca-4d13-adbb-b191182b7e87 · outbound

This paper cites AVD2: Accident Video Diffusion for Accident Video Description.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models AVD2: Accident Video Diffusion for Accident Video Description

Reference 35

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source=pdf_text observed=2026-08-07T12:43:55.791504Z digest=sha256:db5b001a6ad4c36f36e3a277e8e53b2ea54c62efe5cc7a566a47ef2e41067bb4

Observation 0164c948-f712-4a29-bc9a-816a9a0a1e33 · outbound

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

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Enhancing End-to-End Autonomous Driving with Latent World Model

Reference 36

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source=pdf_text observed=2026-08-07T12:43:55.915576Z digest=sha256:804fcbed5b3c89a772b5afaec9151f3af68587ea78e7bf3b6556d055691712b4

Observation 229fed82-a5b1-4018-a3ad-5abc1885bac8 · outbound

This paper cites Is ego status all you need for open-loop end-to-end autonomous driving? 2024.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Is ego status all you need for open-loop end-to-end autonomous driving? 2024

Reference 37

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raw_fallback, observed 2026-08-07T12:44:05.860962Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.024688Z digest=sha256:1195b017beb0de56f17e8a1fdf0184eb167631c9a531b2f3f0e9990306c0cc66

Observation e71fedcd-2e9b-4f44-8409-b1a0e40fa1a3 · outbound

This paper cites Detecting the unexpected via image resynthesis.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Detecting the unexpected via image resynthesis

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:05.763750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.126520Z digest=sha256:2e32aa8f122a2a9cdd893c22169cdc652d297a80970a6987dbe25245454fe9b9

Observation 628b128c-94a6-47d4-ba42-02873735dabe · outbound

This paper cites Visual instruction tuning.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Visual instruction tuning

Reference 39

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source=pdf_text observed=2026-08-07T12:43:56.188348Z digest=sha256:c998e28a75809f26c1bf5ce7eae4d450674984f6fbbb64421bfd2f817e9761b3

Observation b409e9d3-1593-4dc3-bbb6-43de91bf6fdf · outbound

This paper cites Neural rendering for safety-critical autonomous driving simulation.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Neural rendering for safety-critical autonomous driving simulation

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:05.548782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.271318Z digest=sha256:69f9c520128800873782edcc2b51ae005d403aaccbe49a48c3b488700dbd2c09

Observation a0da2bbe-dcf4-4da6-ba34-a4f65753fcff · outbound

This paper cites Neuroncap: Photorealistic closed-loop safety testing for autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Neuroncap: Photorealistic closed-loop safety testing for autonomous driving

Reference 41

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source=pdf_text observed=2026-08-07T12:43:56.331487Z digest=sha256:6bf7dcb6a48f6659366506bb9dfde370ea4fc396e4a8df8d51ed8db70366fbde

Observation 8f331ab6-1af1-49d9-bd5a-9f09b1801d9a · outbound

This paper cites One Million Scenes for Autonomous Driving: ONCE Dataset.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models One Million Scenes for Autonomous Driving: ONCE Dataset

Reference 42

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source=pdf_text observed=2026-08-07T12:43:56.359232Z digest=sha256:c76442b4e1bfe526d79b450241dba5324ac65ddef802ebd80453f11e2ff79aa8

Observation 4041c266-621c-42d7-8e48-fba32bc83a06 · outbound

This paper cites The mapil- lary vistas dataset for semantic understanding of street scenes.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models The mapil- lary vistas dataset for semantic understanding of street scenes

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:05.295738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.425385Z digest=sha256:fa792a7a6f5656ad920e43aeb366e903aed146a696b9303a152a4dba212c1d23

Observation 377628ad-4d54-44f5-8214-9642b75d28cb · outbound

This paper cites Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving

Reference 44

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source=pdf_text observed=2026-08-07T12:43:56.466434Z digest=sha256:01f51e178d1c1341db4d974e94c88707569d99511fca015d28049532d03e98ad

Observation 389c19ae-5645-4c05-908d-0cc03e313712 · outbound

This paper cites Lost and found: detecting small road hazards for self-driving vehicles.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Lost and found: detecting small road hazards for self-driving vehicles

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:04.991770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.494282Z digest=sha256:492236be30dc546f2b3d150bef12e7c9cfce549f0c704590643d005484eab5e1

Observation 0499c0e7-4f10-46b7-a299-020ad10c332a · outbound

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

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Multi-modal fusion transformer for end-to-end autonomous driving

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:04.841677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.534206Z digest=sha256:9dc5710aa714c7fead68389037d47c002d3247b0205e7e27ad078f250e9c089c

Observation 97962e97-d92c-4f8e-984b-a80e9762097c · outbound

This paper cites Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:04.727691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:56.578100Z digest=sha256:263ec268126f5e372d60955d4778baf1e4f94aaaf1fa715b5690fdec31f752c7

Observation b99bcb2a-0662-426e-b7c8-9dccab1880b7 · outbound

This paper cites LightEMMA: Lightweight End-to-End Multimodal Model for Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models LightEMMA: Lightweight End-to-End Multimodal Model for Autonomous Driving

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:56.629156Z digest=sha256:3bb31fd45a6428d208e642272271f9b21435319f4c33b039ad7877674528f05d

Observation 5baf5823-14b8-44c1-9e4f-11da0a087384 · outbound

This paper cites LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving

Reference 49

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source=pdf_text observed=2026-08-07T12:43:56.671998Z digest=sha256:50a94270197c45de2891daa0b5e774b5e57324b91fb7e27877fe0f523809ddac

Observation c959f8f4-9225-4e74-a87d-850c9559fbe2 · outbound

This paper cites Lmdrive: Closed-loop end-to-end driving with large language models.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Lmdrive: Closed-loop end-to-end driving with large language models

Reference 50

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no resolver link, observed 2026-08-07T12:43:56.725639Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:56.725639Z digest=sha256:bf8bd7cbe7e1fb29521523c2450d12a5b4608a46d33e8591e6b937a506c337aa

Observation 06d11cc3-e510-48b2-b56c-3f6bd2a80e7f · outbound

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

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Reasonnet: End-to-end driving with temporal and global reasoning

Reference 51

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no resolver link, observed 2026-08-07T12:43:56.754304Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:56.754304Z digest=sha256:340c7a7b0de2b7089e67df1e56206ea2a09e9bdb0b751167c374422192b0e00d

Observation a5e9a7e2-7ccc-4ab9-a62c-0b6a9c4c1180 · outbound

This paper cites Drivelm: Driving with graph visual question answering.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Drivelm: Driving with graph visual question answering

Reference 52

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no resolver link, observed 2026-08-07T12:43:56.789276Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:56.789276Z digest=sha256:97c95193f0dea01c5e9da5682e6638e71d50018d0c56ef001c0ee7512057804a

Observation 693779d1-1163-444d-9fa1-52bc156838c0 · outbound

This paper cites DriveLM: Driving with Graph Visual Question Answering.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models DriveLM: Driving with Graph Visual Question Answering

Reference 53

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no resolver link, observed 2026-08-07T12:43:56.830698Z

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source=pdf_text observed=2026-08-07T12:43:56.830698Z digest=sha256:0ef5905972acd908822be97aaf697210273241243572391b6e155ebf0b87bbea

Observation faf08ad7-6753-4a9d-9fab-24146458e038 · outbound

This paper cites Insightdrive: Insight scene representation for end-to-end autonomous driving.arXiv preprint arXiv:2503.13047, 2025.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Insightdrive: Insight scene representation for end-to-end autonomous driving.arXiv preprint arXiv:2503.13047, 2025

Reference 54

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source=pdf_text observed=2026-08-07T12:43:56.871535Z digest=sha256:ee9973183e273499abb4192ad67e62980418668a56f3cbdfac8d3f1b4ca9ee02

Observation 83099bf8-25bf-4237-9a25-d55124355e34 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Scalability in perception for autonomous driving: Waymo open dataset

Reference 55

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no resolver link, observed 2026-08-07T12:43:56.922519Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:56.922519Z digest=sha256:ed38e14fed82f4327bab57e78114683c31ba8d617ace16f3c4590b44fcfc903d

Observation f9e89ca9-19a1-4480-ab14-5b7d33608605 · outbound

This paper cites Latency-aware Road Anomaly Segmentation in Videos: A Photorealistic Dataset and New Metrics.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Latency-aware Road Anomaly Segmentation in Videos: A Photorealistic Dataset and New Metrics

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:44:01.240050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:57.001005Z digest=sha256:f5e5c80d007ff262aa9e10aca8262f0f8ea9af62ead683edf6b5d784d454fab6

Observation 24c18685-4ae7-4b05-9f51-2a61d2161c10 · outbound

This paper cites Unsuper- vised road anomaly detection with language anchors.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Unsuper- vised road anomaly detection with language anchors

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:04.444659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:57.052492Z digest=sha256:995944b18c13eb93c1731f4f025521921eb0e758807c46edfdbbdc8307d923b3

Observation 3bb042aa-f010-41af-9d31-dfffc72f96d8 · outbound

This paper cites DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models

Reference 58

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source=pdf_text observed=2026-08-07T12:43:57.109906Z digest=sha256:2e8d1851a7ee2055b41a21ff218f2d5dbb7b1548a06e19c9699bbd1ba8a3c123

Observation 20605ac9-5371-4d48-819f-a689e83e7f7d · outbound

This paper cites Idd: A dataset for exploring problems of autonomous navigation in unconstrained environments.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Idd: A dataset for exploring problems of autonomous navigation in unconstrained environments

Reference 59

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raw_fallback, observed 2026-08-07T12:44:04.255625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:57.172552Z digest=sha256:529106987ba549a9790796c678c69985254ef542f05f67cb7aca9255a49778b9

Observation d99dcaf8-c3b3-465f-a08e-c7de6f248c2e · outbound

This paper cites He-drive: Human-like end-to-end driving with vision language models.arXiv preprint arXiv:2410.05051, 2024.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models He-drive: Human-like end-to-end driving with vision language models.arXiv preprint arXiv:2410.05051, 2024

Reference 60

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:57.268097Z digest=sha256:ecc28802fd6dc54ee6eef10da0d1e17ee03ddf07fa22b454c0cdab316c661f36

Observation 02d85934-b385-458d-8073-fbc9b35054cc · outbound

This paper cites OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning

Reference 61

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no resolver link, observed 2026-08-07T12:43:57.368095Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.368095Z digest=sha256:321825d5d1a3d57593b2ee3705dbaa217cc00a5ba9702393230024237d1262b0

Observation 85d3ba32-1571-42fc-8847-ccbbefcaa5e2 · outbound

This paper cites DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving

Reference 62

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no resolver link, observed 2026-08-07T12:43:57.433245Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:57.433245Z digest=sha256:59a3c079dfab9a328b4750b54e8bac43dbf999f0cd2a40ab0a1685f79e93039b

Observation 430c93e9-6093-44ab-81c8-58fd54fe7e6c · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models CogVLM: Visual Expert for Pretrained Language Models

Reference 63

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no resolver link, observed 2026-08-07T12:43:57.480708Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:57.480708Z digest=sha256:953f8745511ece83ca7e92077afcf63cce1b8d0026776a9f595a01fd82b315f8

Observation 1ef3c976-2370-40b6-979c-f3cebf2f98a5 · outbound

This paper cites Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving.arXiv preprint arXiv:2312.09245, 2023.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving.arXiv preprint arXiv:2312.09245, 2023

Reference 64

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:57.526427Z digest=sha256:11ceeb54e9440794e392e26d446d0f43d68a68d5b99f7c2231bd45029614d89a

Observation 97b848ce-e774-4d42-8097-81e73afa3e3b · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Chain-of-thought prompting elicits reasoning in large language models

Reference 65

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no resolver link, observed 2026-08-07T12:43:57.558191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.558191Z digest=sha256:397606f37977a8cf025074565be0c2412b3d893ceba922453bc4cafc5b418851

Observation d689afab-634d-4c53-bb4b-845a0bdb152a · outbound

This paper cites Editable scene simulation for autonomous driving via collaborative llm-agents.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Editable scene simulation for autonomous driving via collaborative llm-agents

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:04.075517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:57.602657Z digest=sha256:1b2631e3b4f11bd701606c8577b983ade26abbd311f8ca196d72011f5e25660e

Observation 4d728ed0-ecb4-4c05-b480-82fef08963d9 · outbound

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

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Para-drive: Parallelized architecture for real-time autonomous driving

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:03.980566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:57.667441Z digest=sha256:bf1f07258b265e1b447491aa0b8e3b57b3235051f4ab087212a188e60bdd251d

Observation ba8538fc-a862-4b1f-8967-f28846f4bbcb · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 68

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no resolver link, observed 2026-08-07T12:43:57.720414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.720414Z digest=sha256:899de450673f8a9c06ac41cd16d5483bf9e100ff1c61438a399f43a51226e17a

Observation d94c9351-d47f-424a-82a6-98a1e87f28d7 · outbound

This paper cites Referring multi-object tracking.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Referring multi-object tracking

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:03.768803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:57.835861Z digest=sha256:9b250a7e073c198b1f895b49baac12f797bc466b9f0acbc1c49f371e5af1f6b4

Observation d4d4728f-31d8-4f3d-9841-ad1047878d71 · outbound

This paper cites Language Prompt for Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Language Prompt for Autonomous Driving

Reference 70

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no resolver link, observed 2026-08-07T12:43:57.928597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.928597Z digest=sha256:e78a7d869f282d1ce99a1fd71ea134dcb21f0740f9707cebe8384dbd4249ad73

Observation ea3c4b07-d452-49e2-a25b-f1f07e9be472 · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 71

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:58.005230Z digest=sha256:97d9a93f0029e50c5ba8c1d6f3b3c3c441d0a70d0dee660c35b05cb2169882e3

Observation 545dd546-060c-4c70-8f3a-d66925eed465 · outbound

This paper cites Mars: An instance-aware, modular and realistic simulator for autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Mars: An instance-aware, modular and realistic simulator for autonomous driving

Reference 72

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.078421Z digest=sha256:314d3f5395375e8b2de3331f316cad247b3f72dbb3f10dfddc0d6f3528a87d09

Observation 76fdfeaa-9f5e-4d9e-8cf1-77c349b835c6 · outbound

This paper cites Synthesize then compare: Detecting failures and anomalies for semantic segmentation.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Synthesize then compare: Detecting failures and anomalies for semantic segmentation

Reference 73

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.158410Z digest=sha256:02be54b6ea5593ecffdcea0ac081edbf59fdc401e397bee0b4d4ee948cd6637f

Observation 059b7124-7226-493f-a978-a95d81149207 · outbound

This paper cites Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives

Reference 74

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source=pdf_text observed=2026-08-07T12:43:58.249021Z digest=sha256:c86e7b8067b264b82910d52a5696d40bd3d1eda6d6c88a07a88f008d48434d5a

Observation 4941784e-7c03-4e07-b97e-785daa6cd89f · outbound

This paper cites Openemma: Open-source multimodal model for end-to-end autonomous driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Openemma: Open-source multimodal model for end-to-end autonomous driving

Reference 75

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source=pdf_text observed=2026-08-07T12:43:58.324744Z digest=sha256:d8e0fb434fe7655275e4840db1f6526c3819bcad0ca5ffe91c9201d74486f1db

Observation ea5a87f9-cdc6-4251-a157-ce6bb2de8908 · outbound

This paper cites VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

Reference 76

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source=pdf_text observed=2026-08-07T12:43:58.375796Z digest=sha256:b6db4de07fe07637115e31c42054f4934220609890df635778f04b5c2b6678c3

Observation 6ef35f2a-677a-47a8-ae7b-469e6e68eb71 · outbound

This paper cites DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model

Reference 77

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source=pdf_text observed=2026-08-07T12:43:58.419590Z digest=sha256:e44b89c4b56c7d6f20e9bc9f5594f321792dfa66f9652f56e1707e9111629fb5

Observation ef68b084-f74a-4044-b7b7-dea1cf3cc0b7 · outbound

This paper cites Challenger: Affordable Adversarial Driving Video Generation.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Challenger: Affordable Adversarial Driving Video Generation

Reference 78

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source=pdf_text observed=2026-08-07T12:43:58.489169Z digest=sha256:bda4f6ebaab92ebd90ed66302d4102c120a138bc5fe98a06e588a8c2ba8f0d6c

Observation 78fee9cf-bb96-4b43-81b7-9327e759c11b · outbound

This paper cites Int2: Interactive trajectory prediction at intersections.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Int2: Interactive trajectory prediction at intersections

Reference 79

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raw_fallback, observed 2026-08-07T12:44:03.257750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.603947Z digest=sha256:6d52ce4bbdd507ff81d77507b7ee88645c69ec8954653bfd9dad3f2365e3eb59

Observation d3dce658-4871-464d-94a0-4872dff88539 · outbound

This paper cites Qwen2 Technical Report.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Qwen2 Technical Report

Reference 80

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:58.636454Z digest=sha256:616447307242ea5dcc08c05365d5c5f0c0ac786da517b4bfd854ea0257e2e522

Observation 2ef1d802-3bc4-45aa-bb04-09e5aa708757 · outbound

This paper cites Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning

Reference 81

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no resolver link, observed 2026-08-07T12:43:58.705723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:58.705723Z digest=sha256:4d0251f810050347c7d56ee7314a5e7915bd384750247b9d0f2c2cbda380e74f

Observation a5b8b443-997a-4739-9a06-d79bbe3ee7d5 · outbound

This paper cites SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving

Reference 82

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no resolver link, observed 2026-08-07T12:43:58.778472Z

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source=pdf_text observed=2026-08-07T12:43:58.778472Z digest=sha256:0c641fa541404520ef4823dc7d605981e555707d09d4c961d5ce522427f5614e

Observation c4ee4bae-a33b-45ae-b8a8-9b5e6a8433dc · outbound

This paper cites End-to-end urban driving by imitating a reinforcement learning coach.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models End-to-end urban driving by imitating a reinforcement learning coach

Reference 83

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raw_fallback, observed 2026-08-07T12:44:03.049311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.818892Z digest=sha256:b1e6aa20b279023a883bf967c56d82375cdb54f0b52a7df1b3c0390f2643be19

Observation e5ef869a-43b2-4f14-b556-ea1b16459bec · outbound

This paper cites GenAD: Generative End-to-End Autonomous Driving.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models GenAD: Generative End-to-End Autonomous Driving

Reference 84

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source=pdf_text observed=2026-08-07T12:43:58.842298Z digest=sha256:8a73f5dbafbe7f114b6d14e63fa149d6823961978b4c9886a5bbc1083d0a404a

Observation b9df9886-45c5-491a-9e2d-cceedb4add23 · outbound

This paper cites Monoocc: Digging into monocular semantic occupancy prediction.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Monoocc: Digging into monocular semantic occupancy prediction

Reference 85

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raw_fallback, observed 2026-08-07T12:44:02.875702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.878471Z digest=sha256:0a1794f4271289e608cd596eeda87b5056c30d272917eb3c573e008ffe8172d5

Observation 1428ab8d-d32d-4d65-8563-e8e168829ebc · outbound

This paper cites Steps: Joint self-supervised nighttime image enhancement and depth estimation.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Steps: Joint self-supervised nighttime image enhancement and depth estimation

Reference 86

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:02.643517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.919800Z digest=sha256:44b304f9ba1351705d1c5e2d6e79873cdfc5686d35d7dd0ef4f7e7324ee698d3

Observation 2bca0cde-2dad-4c8b-982e-b9facfa11447 · outbound

This paper cites Hints of prompt: Enhancing visual representation for multimodal llms in autonomous driving.arXiv preprint arXiv:2411.13076, 2024.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Hints of prompt: Enhancing visual representation for multimodal llms in autonomous driving.arXiv preprint arXiv:2411.13076, 2024

Reference 87

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:43:58.952462Z digest=sha256:8e410f84db5b853b4bf21f8133c1934df3dc5f2a564020f23c713434779c0c17

Observation c4cdcc59-5205-4585-b33a-c833d043cbc0 · outbound

This paper cites Embodied Understanding of Driving Scenarios.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Embodied Understanding of Driving Scenarios

Reference 88

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no resolver link, observed 2026-08-07T12:43:58.997932Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:58.997932Z digest=sha256:fbc3b72e9bb9527ab7efe108c7ef79a1469bbd3edb995f11ad1056e9248bc4e7

Pith citing papers

Observation ae9035c8-cebe-40f7-8752-3275413763fa · inbound

A Survey on Vision-Language-Action Models for Autonomous Driving cites this paper.

A Survey on Vision-Language-Action Models for Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 18

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source=pdf_text observed=2026-08-06T21:31:04.384791Z digest=sha256:48183cfe5c3d22d4144f8ad32fa527793e655ed161c693f1d4645bebc6aadd40

Observation 196d0325-5a3a-45f0-8a4f-148bbc2a9828 · inbound

TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Models cites this paper.

TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Models Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 34

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no resolver link, observed 2026-08-04T21:29:09.319498Z

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source=pdf_text observed=2026-08-04T21:29:09.319498Z digest=sha256:0121709375f7efeb2de0535d6f8599ac2e8b445ce8f7137a9c6981d4c9c5f425

Observation 5c04cba9-c92c-419f-8919-09e294d9f439 · inbound

RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation cites this paper.

RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 16

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no resolver link, observed 2026-08-04T20:10:13.346389Z

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source=pdf_text observed=2026-08-04T20:10:13.346389Z digest=sha256:2346d9aba7415cfcf2cf048b2c6be8b1c3850e11ab8386d002159ddc6fd06806

Observation 2fd31518-1945-4c47-9f28-8ff102d89257 · inbound

Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey cites this paper.

Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 130

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source=pdf_text observed=2026-08-04T19:19:25.999539Z digest=sha256:4b851445cd87e02bc95d8a3e0fac903bdf91c1b05e5b846ca94ea702148c74da

Observation 1f7b0815-e253-4a45-8645-c237db0073a8 · inbound

OmniNWM: Omniscient Driving Navigation World Models cites this paper.

OmniNWM: Omniscient Driving Navigation World Models Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 11

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T08:57:06.465834Z digest=sha256:51c86f77b5376c798beb1af08631582247a7ca2dea5a529188edb737abcf77cf

Observation 6ece5e9a-6bc4-4cb6-831b-a8860fccd60d · inbound

Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail cites this paper.

Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 8

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metadata mismatch
arxiv_id, observed 2026-05-18T02:35:13.234197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T02:35:13.126171Z digest=sha256:71d45f8a7d0fc8216f769ea4b049c908b00b98cafdf82585cfc6ba6b59b634a2

Observation f66ab2f8-169a-4d0e-9e54-7b985db40f93 · inbound

A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach cites this paper.

A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 13

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source=pdf_text observed=2026-08-03T16:52:50.875760Z digest=sha256:d7e7f18f09657fb3c4a345064fead4a356425eda701909440b00b1ee7b166159

Observation bf88cfa6-ffb5-41e2-be72-78f8cca2a231 · inbound

An interactive enhanced driving dataset for autonomous driving cites this paper.

An interactive enhanced driving dataset for autonomous driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 49

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no resolver link, observed 2026-08-02T21:19:52.228992Z

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source=pdf_text observed=2026-08-02T21:19:52.228992Z digest=sha256:a94282833de1d627b81b18de0b1731a35210b93a505c78001e046ce5692bba77

Observation f1bf4274-ba9d-4722-af5d-70e5225b7d90 · inbound

NoRD: A Data-Efficient Vision-Language-Action Model that Drives without Reasoning cites this paper.

NoRD: A Data-Efficient Vision-Language-Action Model that Drives without Reasoning Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 6

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source=pdf_text observed=2026-08-02T21:12:24.280721Z digest=sha256:4ff4cd485b257fb1df0cbd1b156bd52786f14cc39f2c834f8936d699e85206ae

Observation 96755b8f-5a6b-47f2-9dbc-ff4a36ee3874 · inbound

EvoDriveVLA: Evolving Driving VLA Models via Collaborative Perception-Planning Distillation cites this paper.

EvoDriveVLA: Evolving Driving VLA Models via Collaborative Perception-Planning Distillation Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 3

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metadata mismatch
arxiv_id, observed 2026-05-15T14:15:54.611568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T14:14:45.982490Z digest=sha256:36e8319c1ae88814f9e4631a696c9a86efa566e4ae1c4600472af1c2b41d90ff

Observation dc71aff4-7332-468f-935f-4088eb4fccf0 · inbound

DynFlowDrive: Flow-Based Dynamic World Modeling for Autonomous Driving cites this paper.

DynFlowDrive: Flow-Based Dynamic World Modeling for Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 6

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metadata mismatch
arxiv_id, observed 2026-05-15T09:09:53.310593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T09:07:01.727331Z digest=sha256:b462fd623d0dc3743510d30f33ea0efe748226cefcdaa3f4cae5431f517940fc

Observation c10fb34f-1770-4aa9-be17-16998f63e453 · inbound

Learning Vision-Language-Action World Models for Autonomous Driving cites this paper.

Learning Vision-Language-Action World Models for Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 16

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metadata mismatch
arxiv_id, observed 2026-05-11T07:31:00.784336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T17:08:10.442655Z digest=sha256:7f9bb66df3faaa63e419f62b2150c73e33ab71468aa344899cd14dd7eb66f162

Observation 102e638e-1929-4de6-b939-7ec014fc23f3 · inbound

OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models cites this paper.

OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 11

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metadata mismatch
arxiv_id, observed 2026-05-11T11:56:25.641365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T04:27:24.653711Z digest=sha256:5600e2f2c59b5020d51c15ed0cd5ead5db76f8a709e89f33aa23974452b042df

Observation 18343ed0-f8e3-4702-9396-71794fb63389 · inbound

Steadily moving semi-infinite fracture in plane poroelasticity cites this paper.

Steadily moving semi-infinite fracture in plane poroelasticity Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 17

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verified exact
local_arxiv, observed 2026-07-05T11:41:02.538983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-05T11:39:05.686584Z digest=sha256:3b5aced39485d3fdb85e891785ed9d4d22c4a6873df9971208323891f396ada9

Observation a57e6d60-440d-49cd-b71f-72e0af0f88c8 · inbound

XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments cites this paper.

XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 17

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arxiv_id, observed 2026-05-10T05:51:10.265223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T05:46:36.865150Z digest=sha256:ec5cc95d9a4ec8121c15173b22042a0e68fd160433288f5764d5e7d887cd6ecd

Observation 2a6caab4-0303-4337-a55f-79cfb4dd03f0 · inbound

EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving cites this paper.

EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 6

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verified exact
arxiv_id, observed 2026-05-10T00:19:47.186985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T00:09:18.068337Z digest=sha256:9d5fb98cee7148687fc906ad6a1d7b019bd6cf646b6269fd6a2dd640541b85e6

Observation db4d8c7c-7ec7-43ce-9cc4-f1f3239dca43 · inbound

AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation cites this paper.

AsyncShield: A Plug-and-Play Edge Adapter for Asynchronous Cloud-based VLA Navigation Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 21

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metadata mismatch
arxiv_id, observed 2026-05-11T22:11:13.827738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T03:18:03.855477Z digest=sha256:2a27b4fe9d6dba55824186c15dcc5873e5b63ba27f40d972770253ebaae702d9

Observation a2f4e5b7-4af1-487a-b581-34cec67da7b9 · inbound

MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving cites this paper.

MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T20:59:28.107280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T20:54:50.887381Z digest=sha256:bcd93422457d989b187ad907d0618f83a500f137626d93d6146f14fc98bdb041

Observation ce5fa6dc-884f-491f-a29b-7d7767cbc6ee · inbound

MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving cites this paper.

MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T05:09:45.382811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T05:07:58.953866Z digest=sha256:4db15119a10feae2c46512111d863e2de9b52d471fc30d7544ca5bf7dc64ac35

Observation 5d1bdaca-ec1a-45c0-abb1-3e0d717c4206 · inbound

CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning cites this paper.

CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T20:59:01.699297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T20:57:06.455108Z digest=sha256:d7d157642571e0b6cdf47e35b0010a09394dfc96e67974d037a2c10fb0ebc415

Observation eb88c94d-c203-4732-8dd5-2b3ec0f04ac8 · inbound

Grounding Driving VLA via Inverse Kinematics cites this paper.

Grounding Driving VLA via Inverse Kinematics Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:33:58.357428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T05:33:34.750047Z digest=sha256:ba4a59717a78abe02a586aea09b9d0d18c86763dd52ca8f6d66ba9416252fb56

Observation 060aea4e-8b4d-4cac-8f62-43a0d117a65b · inbound

Does Visual Information Play a Decisive Role in Vision-Language-Action Model Driving Behavior? cites this paper.

Does Visual Information Play a Decisive Role in Vision-Language-Action Model Driving Behavior? Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T22:42:46.544305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T22:39:32.487156Z digest=sha256:678a76e04afe246c318747d09827d888e674d76c327a3c390931c55bf70bc712

Observation ad0db585-6a53-4775-9363-3f47ad8aa934 · inbound

nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving cites this paper.

nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 57

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:26:00.310988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T22:35:04.552901Z digest=sha256:821bf7b3c8a0a1b3f3426e331c8e386429069cf34fc79cbfba277224779968dc

Observation 2675bb56-f3c4-435f-98cb-17f099b597ca · inbound

GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving cites this paper.

GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:06:19.763326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T14:45:54.904876Z digest=sha256:ce277d97f24723baecd544fe7312c9254b83581f7e6cb2519c78333c0d4a27c1

Observation b36d16e5-a5a3-4960-ae6f-89b354f46b6a · inbound

EventDrive: Event Cameras for Vision-Language Driving Intelligence cites this paper.

EventDrive: Event Cameras for Vision-Language Driving Intelligence Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T20:18:57.106030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T01:26:43.752335Z digest=sha256:43c8e6bf3b558bcbd9bf007f764fb6eb9a83c3e9260aa1a6eee9e8720fc93611

Observation 40521f0b-87c1-4641-8430-fd7a0260f15d · inbound

Teaching Vision-Language-Action Models What to See and Where to Look cites this paper.

Teaching Vision-Language-Action Models What to See and Where to Look Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T16:48:39.587385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-03T16:42:13.520913Z digest=sha256:0142bb18fe646e2046983ce4ea4844e6fb57359531e76b5a39ac28adb8a8660d

Observation 7c17c601-7636-4dc0-9aef-31e85dd41760 · inbound

A knowledge-augmented dataset of high-risk driving scenarios with LLM annotations for autonomous driving cites this paper.

A knowledge-augmented dataset of high-risk driving scenarios with LLM annotations for autonomous driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-07-09T20:16:29.462683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-09T20:11:02.051543Z digest=sha256:ba65913c4b57159cd2382923a34ff58757bfa01dcb5b268b8e3cae741527d084

Observation 866d70bb-612c-4630-b88e-85afed4dc9b8 · inbound

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving cites this paper.

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T08:36:59.863731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-10T08:30:29.351159Z digest=sha256:5e0ee8e2f0fcb81d8d42a27bd08759ddd6c984c8c0471c9345c9b69eb3f92863

Observation de6d88e8-cce2-4956-9193-a8291c402400 · inbound

PrismAD: Decoupled Planning via Semantic Mixture-of-Planners for End-to-End Autonomous Driving cites this paper.

PrismAD: Decoupled Planning via Semantic Mixture-of-Planners for End-to-End Autonomous Driving Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-14T12:33:06.583512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T12:33:06.583512Z digest=sha256:018272025d62785ff8cd689022f8d3043eea12fbff6de6e5ff002f4483e663ae