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Paper Citation Record · LEDGER

NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2504.03164.

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

pith.paper-citation-record.v1
2504.03164 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:02:13.111100Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:06:20.242744Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation bb8925f4-fb50-4f58-8bc6-6e3acc12d6ab · inbound

STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving cites this paper.

STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T06:02:13.111100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:02:13.111100Z digest=sha256:dc7403c4272969af6bfbad5dfd1115ea7cf572f979faa23cd2d180224e5b9ebc

Observation 5936f377-c691-493d-b50d-4cd6b3d77a84 · inbound

AD^2-Bench: A Hierarchical CoT Benchmark for MLLM in Autonomous Driving under Adverse Conditions cites this paper.

AD^2-Bench: A Hierarchical CoT Benchmark for MLLM in Autonomous Driving under Adverse Conditions NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T04:49:28.914410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:49:28.914410Z digest=sha256:c655af6b02cc7cfc7768910cda7be70acf54759cab3abae085f94c25429d463f

Observation 93f5f79b-3459-47a0-bf28-ff0aca00eeb0 · inbound

AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning cites this paper.

AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:46:44.013090Z

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=2026-05-14T21:46:43.955825Z digest=sha256:198c2b2317e0345e51b066f9c13c1277414a1849a23329913f0bc623f16d7e46

Observation cabeb626-d188-4fa2-b1b4-c3e129bbac8c · inbound

Automated Vehicles Should be Connected with Natural Language cites this paper.

Automated Vehicles Should be Connected with Natural Language NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T21:48:54.924418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:48:54.924418Z digest=sha256:96698ca52734c22410bda18a07a1ba6fd9c7d6044c3e2fe33af848feecc78fb4

Observation e5ae5bd8-828b-4180-956f-b91730f0c582 · inbound

From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models cites this paper.

From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:50:47.278451Z

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=2026-05-21T23:49:59.795575Z digest=sha256:1810474ac3d9670375b83e7eebb0b25e26bc364ac665ff710ae345db4fa29dab

Observation 9070cceb-3789-40a8-a321-3d5a5097dc80 · inbound

Understanding Space Is Rocket Science -- Only Top Reasoning Models Can Solve Spatial Understanding Tasks cites this paper.

Understanding Space Is Rocket Science -- Only Top Reasoning Models Can Solve Spatial Understanding Tasks NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-05T11:56:10.918290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:56:10.918290Z digest=sha256:60ac14bd08c18ac8371b088e21630c0169fd96ac6a8e46654dd46a616c145fbc

Observation 1cd4cf48-51b0-47fe-84ff-bf190e261f57 · 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 NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 85

Resolution
verified exact
arxiv_id, observed 2026-05-18T02:35:13.238965Z

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:a6e666b5c5d04f3165a960ca7a8518e670f31fcfa5aa15256597dba4f5c33ffe

Observation 0ed634ff-f6e0-4037-8e01-a0acee736260 · inbound

MonoSR: Open-Vocabulary Spatial Reasoning from Monocular Images cites this paper.

MonoSR: Open-Vocabulary Spatial Reasoning from Monocular Images NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-03T20:38:56.380114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:38:56.380114Z digest=sha256:e1b909d9f3d6c7d9bfd85b6a483ef5c996ac36f3978c17a4aeac1b56d03292c7

Observation ba5681dd-7960-4f7b-a14f-8116b119234d · inbound

Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation cites this paper.

Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:40:33.132144Z

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=2026-05-16T03:39:28.364183Z digest=sha256:3b871e70a48844dffd1e44363ecd06e84c6d889683d23909fdcf11050b005550

Observation e18fb11f-4297-422f-b6d0-1665bf7e9b92 · inbound

More than the Sum: Panorama-Language Models for Adverse Omni-Scenes cites this paper.

More than the Sum: Panorama-Language Models for Adverse Omni-Scenes NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:00:02.914572Z

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=2026-05-15T13:58:18.635091Z digest=sha256:4af1ba36b08e85972a0417f895842877cfd697d0de12a6edd8e8e1b95c199f1c

Observation b9f5bd5d-150b-4d3f-8a96-5b4a1227da10 · inbound

Probing Visual Planning in Image Editing Models cites this paper.

Probing Visual Planning in Image Editing Models NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T14:31:06.715261Z

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=arxiv_source observed=2026-05-09T21:40:23.460129Z digest=sha256:dd199f0d0a7f60a2b202899f145df042247d24aebed5ec582ca178959cbbac1c

Observation 98677b79-a496-4850-a7e3-4a92897c09d0 · inbound

Lateral String Stability for Vehicle Platoons: Formulation, Definition, and Analysis cites this paper.

Lateral String Stability for Vehicle Platoons: Formulation, Definition, and Analysis NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:01:00.987754Z

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=arxiv_source observed=2026-05-10T16:17:51.079919Z digest=sha256:b121bcaacce577ba37ca084b8ef3c489882645bb71891f18fff09ba02df87dd4

Observation 210f0e99-0606-4a46-b340-3e8afc6b6d0b · inbound

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving cites this paper.

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 115

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T06:31:26.534656Z

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=arxiv_source observed=2026-05-12T04:13:37.421188Z digest=sha256:dd9e394672d1983e84c79589ea64534611a56de1a03d8071e56ca7e9567773a8

Observation 30ff18dc-de0d-4e68-9cc5-7f8af7d97d35 · inbound

DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.

DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:15:22.970050Z

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=2026-05-25T05:10:32.522453Z digest=sha256:2162660dc3ea4d7968635d5c0245ad4633c0d77d43855a5cb1224df98db9abc4

Observation 656104bb-f775-47b5-86da-31557de501c6 · inbound

DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.

DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-06-30T16:44:56.038675Z

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=2026-06-30T16:40:22.441025Z digest=sha256:dc8b42d217e364cb778859b1f98540dcfaf982d65f877dd16563a682c18814fb

Observation e9d7fd76-9f6d-4eb6-b8df-bfdc99b7ddf9 · inbound

Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View cites this paper.

Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 60

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:06:20.244880Z

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=arxiv_source observed=2026-06-28T14:42:47.815192Z digest=sha256:734963d98a9679d1e8ff378b820ab4fa86a56de1237c79c5dc9a8c028d3135f3

Observation 3849e7db-01bc-4f92-9a52-7b3d68c22b2a · inbound

Deferred Exposure of Future Trajectories for Verifiable Reasoning in Autonomous Driving VLMs cites this paper.

Deferred Exposure of Future Trajectories for Verifiable Reasoning in Autonomous Driving VLMs NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T00:13:54.468344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:13:54.468344Z digest=sha256:5f54a18ce52b714a976d4d07605d4800c3fd4d1ebd750b128f8254180086783a