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Paper Citation Record · LEDGER

NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2305.14836.

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

pith.paper-citation-record.v1
2305.14836 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:37:05.336661Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:09:44.900708Z

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 4e3329d3-84ce-43ef-8aab-74a733011334 · inbound

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

DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-12T19:22:35.476752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T19:22:35.305220Z digest=sha256:0a71ba0bd86e54777a64755fc3d6f44427ffcb53b76adf0723170ece9a4dd3c3

Observation 3ed0901f-d86d-46c9-9633-97935a4e0758 · inbound

CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning cites this paper.

CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:37:05.336661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:37:05.336661Z digest=sha256:a54c961ae12016241a342b60facb2f42c44fda6c488173f45f553c02912d7637

Observation 32d4c2d8-6703-42a8-9cd3-9e62123a26fc · inbound

VRU-Accident: A Vision-Language Benchmark for Video Question Answering and Dense Captioning for Accident Scene Understanding cites this paper.

VRU-Accident: A Vision-Language Benchmark for Video Question Answering and Dense Captioning for Accident Scene Understanding NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T17:52:02.716601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:52:02.716601Z digest=sha256:48c383ba684723d3db9fc0ef97f1210e0f45f4847de68079a98f02fa0c1a1932

Observation e5f7465c-63d7-4549-83db-691b68c40cc8 · inbound

MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding cites this paper.

MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-06T16:49:52.051367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:49:52.051367Z digest=sha256:4833799d1cb113501db2c7b7ad3df28ab8ab22b6fdce29a15ccf44e2c7a7291c

Observation 4a83accd-7736-47fc-b9b8-8412133f3d4f · inbound

B4DL: A Benchmark for 4D LiDAR LLM in Spatio-Temporal Understanding cites this paper.

B4DL: A Benchmark for 4D LiDAR LLM in Spatio-Temporal Understanding NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-19T00:11:55.984627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T00:09:57.236162Z digest=sha256:fdf3cfae3792cc926acf0221868ef136495aebd7741de83dc219ae4fe0686654

Observation fa72e42c-1ba1-4ad4-80ee-dff96d097af0 · inbound

DriveQA: Passing the Driving Knowledge Test cites this paper.

DriveQA: Passing the Driving Knowledge Test NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-05T13:58:09.891547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:58:09.891547Z digest=sha256:5bfab98cef435ad217885167b46bb4a22a2a6d874f1ea0bcb06140fb258c3d4d

Observation 13e3831e-9614-4690-ba98-ee0b040980e0 · inbound

Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment cites this paper.

Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:41:23.559754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T17:30:39.410040Z digest=sha256:5b80d06438ac315461ff3fc2466b6bd4980acf7030a06ee337c5bbfc26880c0c

Observation e808e73f-de4e-4c0d-82e7-287cc820b29c · inbound

CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs cites this paper.

CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:31:05.483773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T01:31:40.267429Z digest=sha256:a427d2bf1c9365481a725512d7905140ec8948dbe8e5f2754e9b4c3c1d5cfb6a

Observation 9aebf29a-6dbe-4480-ac5e-4e5c624bdb9f · 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 NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:19:47.199716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T00:09:18.068337Z digest=sha256:3ac55f1c57c0cbee4e38621c96b70ace6060ad2b87ff1e374582051804aafd6f

Observation 4775a4ba-8af9-42c0-962a-830b9bc03616 · inbound

FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages cites this paper.

FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 32

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T06:49:37.371768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T14:14:23.976821Z digest=sha256:b7c508758b61994756fb88466034805bd1b472302fbe0a90b679c6ef7934e25d

Observation ffd9be8a-5c0b-4bf5-a03b-bf393a771b53 · inbound

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving cites this paper.

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:09:44.902173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T09:06:54.669489Z digest=sha256:0faacbe01c9384cdcad0decb359e5c9771935d3221e7d6d9351805c6ab485fdf