Pith. sign in

Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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:aa3dd16c8398d245745d5a14cd7813cf3665265362670b86f3b82b734bc27365

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=sha256:2181725a8fbd4817f2ac158a5a453aa4aa25f5aba2ab2b81da3ced4e3f557a63

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T21:46:43.955825Z digest=sha256:84a2a785497355273318795ac33f7c5b5553fec2c90b0255181045cfaeabbe30

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:da2e3d040550d783c3bca4594c6fe6a15ab7b81e97038d92139d8058cb797a16

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T23:49:59.795575Z digest=sha256:f015fccce0273b3c0a6be2dfaebdfbcc6220bdf2917e00a3edd1810b44925423

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:ed99b2a543643fbe30f24dedfb1e87cdc7fc355967487873f9e9386afbc8ff9d

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T02:35:13.126171Z digest=sha256:e96fd5de94a342bf51610ec2396d41df645386acf064b32be50ffdc264e25de0

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T03:39:28.364183Z digest=sha256:0b59afc2c00492ff9ac4ad6abffab5260f74ca13b5472d13bee6698a6137ab7a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T13:58:18.635091Z digest=sha256:5234f2a1f9c967a9c495f916dd5281123a07bd788c72a0cdadbe22269deb4ad5

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-09T21:40:23.460129Z digest=sha256:9eaff2813bafba30b7b96266304a16ce57a9aeeda1216b374d8b4dd8ed8dd5c9

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T16:17:51.079919Z digest=sha256:6287a20f7842a0a0e6f2457f3e4f9fc43a5b21282e4ba6aa7ec71754b2bd0489

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T04:13:37.421188Z digest=sha256:f35a0cf3099f9949f35bbf0490721c93207a38608a920658d206bee5e5ded773

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-25T05:10:32.522453Z digest=sha256:76fb909fde1754b15563b4591d6f305c90e2749b6a705aa1ff1003d9df40e9ef

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T16:40:22.441025Z digest=sha256:d67b7e7202bba8cbdde2b88f9cd88960e80a8e6e923a1b45be09f337891ab562

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T14:42:47.815192Z digest=sha256:0df95cd7f26fb3b2ac5bfb93f81a1da614beaeb21d8be088d036251d82f7ee21

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:ee5292caa017418874acb5d1a45a4066f96dd018395e60501c2f7c386a9a93fb