Paper Citation Record · LEDGER

GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2408.01584.

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

pith.paper-citation-record.v1
2408.01584 v3

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 2026-08-21T06:32:19.484+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:42:09.976892Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:49:38.028458Z

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 8dfd740d-e136-4f10-a72a-2dcf61f958e5 · inbound

Gymnasium: A Standard Interface for Reinforcement Learning Environments cites this paper.

Gymnasium: A Standard Interface for Reinforcement Learning Environments GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:29:49.426309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c2efcc4e-c5af-4f7e-97bc-6197aef73732 · inbound

Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulation cites this paper.

Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulation GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:45.696456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9712ba4f-fdfd-4e72-8ecb-ab5edff2c199 · inbound

Swarm-Gen: Fast Generation of Diverse Feasible Swarm Behaviors cites this paper.

Swarm-Gen: Fast Generation of Diverse Feasible Swarm Behaviors GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T21:36:40.764461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d4849f4-b274-467e-b55f-3ab8db7a3683 · inbound

Towards Autonomous Micromobility through Scalable Urban Simulation cites this paper.

Towards Autonomous Micromobility through Scalable Urban Simulation GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T04:42:09.976892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ba4ff6a-0018-4efd-9257-9ae4ae31043f · inbound

Toward Efficient and Robust Behavior Models for Multi-Agent Driving Simulation cites this paper.

Toward Efficient and Robust Behavior Models for Multi-Agent Driving Simulation GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-17T01:01:24.386667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation efde0166-a934-482e-8d0b-22a8cc33f519 · inbound

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation cites this paper.

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:26:27.502671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 06ea35c5-5a2c-4b9b-904b-b465e2cb1c9e · inbound

SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics cites this paper.

SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:06:28.963189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 00930267-5a84-40ed-864c-64ba1f10a56d · inbound

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents cites this paper.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:07:25.846756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d28f576-a02d-4668-8f56-93da6ecfed53 · inbound

Human-like autonomy emerges from self-play and a pinch of human data cites this paper.

Human-like autonomy emerges from self-play and a pinch of human data GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:28:32.016770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1e0b30c4-b60f-4fbd-83a8-15de8bf409e1 · inbound

FAST: A Framework for Aligned Sampling and Training in Parallel Reinforcement Learning for Autonomous Driving cites this paper.

FAST: A Framework for Aligned Sampling and Training in Parallel Reinforcement Learning for Autonomous Driving GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:49:38.030577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 642b14c9-74ed-4661-a4a8-6f43af4c2e3a · inbound

FAST: A Framework for Aligned Sampling and Training in Parallel Reinforcement Learning for Autonomous Driving cites this paper.

FAST: A Framework for Aligned Sampling and Training in Parallel Reinforcement Learning for Autonomous Driving GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T17:36:19.344296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.