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Paper Citation Record · LEDGER

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

As of 15 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 2026-08-15T06:32:42.880941+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=sha256:68aa60bd21ec8862c05b77ce8ecb9efdfdad415c2f6eaec86c57db35cb92a1e2

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=sha256:4a3376df51d44418a6bcace3d4f0d05ce61dd8103befc9296d5af9fbdcb94667

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=sha256:65f877b29873e56e59eb4c319de9e2907ade8fa57d16eb53b991d675365fafd9

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:da43efe97181f136a6b5fa2b2037760155bcbc3ad02c034c080273103f68dcf5

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=sha256:0c9dfcac572410731f741cf36d70b62edc2a43d3cd2b0e60344b2582622767c5

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=sha256:6176e12c39cad21b058f4452d95f7c07d62cf8f4070fe1f8972fa30e0a350564

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:e608e486e424c4bbc40bb907d46a7326890a4373aa32c033a3806824f55cef5e

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=sha256:12ea1faddbbcf4a46f598e524d10215d225095936476e1603be3d940eae4c17b

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:fb2bb5155756dbf7a62823caeaf58a6bcecc10d156d9c9693adce72158baab2c

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=sha256:36a3d31801e1f0f589e10ac1c406345ebfcb85d1e1c11d7a5702bc5a8261f29b

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=sha256:389d193c1272f7762ed7286f46dcca101aba3bfafb10c9fa62f4aefa8d4b2ddc

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:d8ce8c869556fe50aa0c296d3d4c0c37e19bf38fc7b5f5dcffc725ed59bc5dbc

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:afd6a93c0ad45bf79cc623b9a2c7976fd9dbb70cb4d7998a88238e1c7d0c2c9c

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=sha256:0c069ad949028a8ae42c651b7cc5552cc3e55ada5229597ee2e597cec58f5b2b

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=sha256:3b0d117173b62584bf046d52b3235d50d41e9733435428a9d7631ab3ec8f964e

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:e52b9f43e5c0944168e8073e769872ffd6f34782c1039e494110b904e1d4b479

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=sha256:8fc7565084e0dc06691d6db3761825cea997c35f016f5a5a3c804afde3738039

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=sha256:10be6ede1ef7ef5b14d072c3e8d4b2aa4313f6b436f26cd8671a532ce2d811e1

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=sha256:451eeb4e1b52ed42cd053e4d4ee02a76dc1fd75a4ea70ef096846aa8625921e4

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:c5959243d4a98071ed11d34935a00068a53c2ec54e4421057fd4a142b8e061b1

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:54.163868Z digest=sha256:19e62de9c575193fa742b7182fd60f309ca7556674d879256a280c3c8ca16510

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=sha256:2300a7d6fe2e14d2395fcca3fb40fc60cf1bb50b3cbb482d68502e1d67109e32

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:fb508a1ccb0e80d3e129f1f02c23b336c8227e35747aee84765d09d5bbded8e6

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=sha256:769f6c935ff63eb5174a73eeb4cc787c3d0b2bc4819dc657932811e74c93d277

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=sha256:858def8a27d7946fd0c19f42920a982f833e51f210ae5bd031a830772ea9ab5c

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:e924153ef55d5e73773ffde283de2d4d1a81d8336cbfc39145512e857a100345

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:d10fb74927f5707ab6a0a50c7b5cf5b9719b41d57fda2d504401ab4d3d75e026

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=sha256:92288a37bf436c917fbf2e3901b1f7c062acffd768fb98948ff04c3de79769d1

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:55.252353Z digest=sha256:66ebbd62e04341315d0b7af004d22a033882f39b2e1696eec07d1022328d762d

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:55.289844Z digest=sha256:d44c4db406d152e5ee45dd77d3ca3668ac1baa67f2592d6d0b19b90b6f27519b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:55.393975Z digest=sha256:e27c998995cbee89355b465b8e966f8da18ac13353fa06944bf8f3cb8502070c

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:55.528628Z digest=sha256:ee800b8a5160811ad7ec7e411dae0e42691f23ccc2003b9c4073cf8d4b136c1d

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=sha256:502b70f74ef33af0f5d0ec710be7625dbb39d95c0980fc592284dfa5aa326816

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=sha256:6fd59b2f1b978c9bf16c3b10023c80daa34f68a358e92020593c3bd34f7c628f

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:c2ce8d21cc46a25bc64c9aeaf8d3b2a71ca2f6323c42c61ef413eb88f6e3a849

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.024688Z digest=sha256:0d5f754881e1cb36d059c789afef72543e96b459e7a58387b84060a9fd8e4c99

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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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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.126520Z digest=sha256:53d44989e56d437b59e1517953d08f3dee40e00f69987778c4246b50ace3a047

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=sha256:3e087844cb0394013365cf45335914ef3173abd62cd2af210b2e2a9639f42c9f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.271318Z digest=sha256:2c07de2c6d8f5a928791f7e2b49b1752cc42f860d9e923b604d34e5830b3d37e

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:f9d72f8027c4c58391172fe478f3a0f77d342af1c09ca689d8dde1310b97e974

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=sha256:835532c80b13fa17b028d26db7192488edb1b9eddaa05fbe72632b42ac7fe78c

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.425385Z digest=sha256:a865837c15a714ef86734c7370c7aa34845d98f9262df884cb34a5d7671de4cb

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=sha256:72c93102115104dc2938deea2578bea9b61fb223c7395dd95a97721c8896c0bf

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

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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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.494282Z digest=sha256:f88ed8f27986fa620fbc64630a47b9c28ddbe20a21afafb2d3612dbd01968f77

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.534206Z digest=sha256:61e3a1851d8b5abda19318a02f9abf76eed359b0ddf6b2f9578e829e2b1a9610

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:56.578100Z digest=sha256:d471aa24134132db6d53a8eec8230361c3222213bf395c2f8e0595f172d32d00

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=sha256:6b313207d1305f1765b86b5fd6ba4a67e10f30b7dd86b2d4c208cafab502805a

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:dd0e0966e20fbaeb52e81ea289fd9038e70ed533901810b8b484b1f5a3c01bfe

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:56.725639Z digest=sha256:35b07a08f8e5a4e57217a39bf94cb3cb1a32b497704d6ff546b6a1818545a495

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:43:56.754304Z digest=sha256:9242aec2489c655aadbe98f745a986276bb33795c734a188c79c5b2f8e092401

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

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

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source=pdf_text observed=2026-08-07T12:43:56.789276Z digest=sha256:fe6cd594d8b85f949ed62aacff9b634a370df47a2645e2671956ed2267d5f073

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:fa1e3a65d073ee25d8ed547ed18d81424d5b43b6fb9a8f520c4fd1bea9976ea1

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=sha256:5c11112c2950fa64d2e757d87a73431a97d75025c2f338c0fb6493f978d04f32

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=sha256:9127c0b33f2e24109dbdbd5447d0693d44ecc7fc55cbd190e4bedc7275ab9278

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:57.001005Z digest=sha256:66d889fd604991e7d66049b1d47986bacc8a1e85ff60db543c9a9260d5c8083f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:57.052492Z digest=sha256:f6a321cef27d279d6240e49b59874480b524307b95ecb41184c6c3a7076a8571

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=sha256:72e185d17d7596423177705b4438136828269cffacb4508a15fa40f0b4a36fa7

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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verified fuzzy
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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:57.172552Z digest=sha256:1ee807be3b3268db61ebe2dbef36be415b6576cb2095b2f4f349197905e530b8

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=pdf_text observed=2026-08-07T12:43:57.268097Z digest=sha256:af80283d008d32cd11e7a5e47848a54a2b47b6c34deaa7b206593429848077dc

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.368095Z digest=sha256:813de739d3300196d494fe5915bc8fce18b6242585a1906b564b52023446a714

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=sha256:60a2e3ff7ca5690c0a4fff2bf7bf711b51a3a38d9b6f754524f1bc2cad24dc2a

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.480708Z digest=sha256:d53ece5141423861e12edebdc5f7f991c46685d382b9ee4cd6cf77399415accc

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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no resolver link, observed 2026-08-07T12:43:57.526427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:57.526427Z digest=sha256:3634c5b7e3c27defd1572304e08f6e691f56e53531b9366b7c029f4d100d8505

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:e657b038597ad9c1195bf9d6f7476bae3a09e1141008731c7e2c4dfbaacaa71e

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:57.602657Z digest=sha256:81910f03bdcdc97fb337d7dc9e2c81f92d3b54aba782b1414d2649f6004efae1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:57.667441Z digest=sha256:b77476a083d42a795107df122d7b663b64db13d76736e975de1054c6acc3381d

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:c0cc24e46c63ec5a5013e62610a8799b864202484750fe6b673d8487cabf5ca4

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:57.835861Z digest=sha256:2f16f1ea054db46148dc063b1db627b987a6f0c64110f26246916d14445cb5d6

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:a042bdb62c26cfe5b64ebbd18e53b0bee7392d4ea5e4b57cb967dced118581ca

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:f22a0c3d0b635a2659cd56b6b969e4f085b0843253b3bbf8a8f166400f814f4b

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.078421Z digest=sha256:ace09014b4a56e9da27d24c445a8995d16e84d349bc4914c2f371c432c6c77d9

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.158410Z digest=sha256:482280ee878cb5f02ffc04a7a9481706097f54051bb9e2a7014fa4b4f1b60461

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:c90e9ebc6752b1037aaaf33cf71e69fe6f5313ec1994abd378d324b7e88f44fc

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:a9607e9f033c8191ec117bfc9622bdd822194927fedbe4f2d0d640f0bdbb064e

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:c65ae9e8b9907d3d69777f16afa2b722be402c8a1a42c1ea1f3de2cbd75b6f26

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=sha256:0d9fd96bd8860f86dd9fb591ae6b36b4985285b5ab7d497ee849e34f819a7d8a

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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no resolver link, observed 2026-08-07T12:43:58.489169Z

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source=pdf_text observed=2026-08-07T12:43:58.489169Z digest=sha256:d15d5d430f6b55c26e3f5db669d3ca01f6a87807e80525f5dd98ea6e93a5f054

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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verified fuzzy
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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.603947Z digest=sha256:67e753f00390982f458695647b6646277f9711803aebf029ed43f964edd35521

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=sha256:2a4e33e809886cb2a21f52a4ba679c77c46e3af839e5e44e82ab45ce92aeae33

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:fbb2b6c644dc205fdd2a2d63cf5ad57f134181295e1abf301bc89ea722b09627

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:d641a09e51f72bbcc3e564f61a7d37c8ef02347a92c747485a673e6b9097eae2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.818892Z digest=sha256:d1f1aa4fc70d245f2834a36b260fbfc21884288dce70325e6fdca4bf3cb4dabb

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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no resolver link, observed 2026-08-07T12:43:58.842298Z

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source=pdf_text observed=2026-08-07T12:43:58.842298Z digest=sha256:be0b9cd622e6f7af25f283412ff183709274d81f714ea9056574a678e5d85c6d

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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verified fuzzy
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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.878471Z digest=sha256:7fb70c99ca32c573e198c81ef3bfd0c1b4e9b77636d8d79fe103b36841e6f685

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.919800Z digest=sha256:917e06a814b982fc5ce9eb360eda5785b4de87d1c27b23328d0a9fa0abb97d99

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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raw_fallback, observed 2026-08-07T12:43:59.539208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T12:43:58.952462Z digest=sha256:5dfaa4dbafccbb4434cc3e13f94f4e7ca3cceb21dda88aa8d952d1b651fed4ff

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:a3c5096cbe07d86deff18779992abb07d7708e2080b52438f48d1182b43875ed

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=sha256:1a64d2b554de7e2795ff74e20bd675f0fe31c75a5de920b7baa8fe7165b0a6ec

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:ce9f6a642ba94f0de372d90f4da97e6913550128db76ad4cdbf2b88435959d9c

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:e4c59ff3a34ca035dbe86ad1914005f241050598169dfbbd6af305fdf384397d

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=sha256:2271c5a6c500e9521f3b05efcd13ca7b99133b961e38014c0abdb3ad3d687f3b

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:dc5e9030d5d4ba1460ea9d2c4f19e5091a53add70582673afe7d03e7008a81c5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T02:35:13.126171Z digest=sha256:de64a5a87aa2548c0d27459230a5ad349d27d294441b6c6c178cef84d9da74a7

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-reported events for the cited work

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source=pdf_text observed=2026-08-03T16:52:50.875760Z digest=sha256:ec60f4df1d6eab61e0f9890e69be7d7de53f9c8b849fcef1df5833b2dba0732d

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=sha256:3f57448f67add244b9894b7d9e5633771973aa251328254da593d17ab488467a

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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no resolver link, observed 2026-08-02T21:12:24.280721Z

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source=pdf_text observed=2026-08-02T21:12:24.280721Z digest=sha256:2e13b84a439116500743b79ae86301ffe1b4b96e2eddfdb673cfea163b984765

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-15T14:14:45.982490Z digest=sha256:125f08f26577b1993b1588b2929b16f159ab20aaa4b07f7dfe7c2f5c95e8e66c

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-15T09:07:01.727331Z digest=sha256:6a0760d22a5c6f42995252bf29c1dc14cf12a5ce72cc53fa7f01af161dce1e13

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T17:08:10.442655Z digest=sha256:010681efbfd2f76128c32621ed7f29231986d2cec5b80029b3d171f032d7aa4d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T04:27:24.653711Z digest=sha256:8f516bba63100db0ca5927efa74c03af08cc498a12f8d0ce37895cf6ef8ec679

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-05T11:39:05.686584Z digest=sha256:37b5fb0da50e3f58e08ff18cb11cdd9d7f74f12b66dcc60a908c5eed77195fe3

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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metadata mismatch
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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T05:46:36.865150Z digest=sha256:48b2db66c9f7ea56274bc191ad63c0acc3b27c0d91ebd14079e1f07b445f884e

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T00:09:18.068337Z digest=sha256:74b42b808b5541006d33e682d9c24d28f1fb31c4bf4827354a659396b1bbb734

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-08T03:18:03.855477Z digest=sha256:6897a747907ea2768bcd8de6e36177163434551e9b02b352af606b9bdd0819f3

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-14T20:54:50.887381Z digest=sha256:fb5ca3bec93dfca0b64eff93cd607464ce8d4544579babcde93663002a0c952c

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-15T05:07:58.953866Z digest=sha256:678180047fc13284e4fb642fb2b67d4563e0750aff070fd8aaf149085f875074

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T20:57:06.455108Z digest=sha256:8e4db99008f0d8a12bc355060f3d7a776aa07b89d297430323fd083f8e9c3416

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T05:33:34.750047Z digest=sha256:a36f2aae65cc8df7fd6f68181464d89af7780c2897465d5fdd2cd8b616adf46a

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T22:39:32.487156Z digest=sha256:b8bc0bc9f533ac13509d79dcd38395126f4ed56c9a60cada876dd80dd8a64364

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T22:35:04.552901Z digest=sha256:be20711fc3b22ccb181768120a03b7224367b4bb908b0a7c414c2e726a89836b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T14:45:54.904876Z digest=sha256:e2fe3f177ca42970a7bd44f3a88efc6740871c1492fab0b7b1b05264cf6bc59a

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-27T01:26:43.752335Z digest=sha256:df2c4d05f9b262dc92450b2feaed0a501ca9412ff4010e8c17e54a681cbbac09

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-03T16:42:13.520913Z digest=sha256:b0066fa81a40312ece22cc819f0165215ef6b739974e962ca716b8d77834a67d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-09T20:11:02.051543Z digest=sha256:8e77018c63e41d932bc9343aaeb27f3db803dc9d161fc2faab6c5f16c8ed38a5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-10T08:30:29.351159Z digest=sha256:f9bcf4c3ee1629539532429b5f687c504a26d82d6053d52ba9fdafafdeca154c

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=sha256:7a8ec0525f18a62f498a681ba9068d95053abc4b5e01e6433b69f895622e82e1