Paper Citation Record · LEDGER

One Thousand and One Hours: Self-driving Motion Prediction Dataset

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2006.14480.

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

pith.paper-citation-record.v1
2006.14480 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:22:23.823441Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T09:03:10.727429Z

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 010cb3c0-70b5-49d0-876a-b48e4c56c9ac · inbound

NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles cites this paper.

NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles One Thousand and One Hours: Self-driving Motion Prediction Dataset

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-15T09:03:10.729650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation afaaa2d6-4136-46db-8c3a-708b8b7aa362 · inbound

Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting cites this paper.

Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting One Thousand and One Hours: Self-driving Motion Prediction Dataset

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-12T20:16:37.429851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e7672975-7931-4254-8836-7e44883e5118 · inbound

TopView: Vectorising road users in a bird's eye view from uncalibrated street-level imagery with deep learning cites this paper.

TopView: Vectorising road users in a bird's eye view from uncalibrated street-level imagery with deep learning One Thousand and One Hours: Self-driving Motion Prediction Dataset

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T12:22:23.823441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3af2f523-f1cd-4096-b8ff-9eba6f8e419b · inbound

Processing and Analyzing Real-World Driving Data: Insights on Trips, Scenarios, and Human Driving Behaviors cites this paper.

Processing and Analyzing Real-World Driving Data: Insights on Trips, Scenarios, and Human Driving Behaviors One Thousand and One Hours: Self-driving Motion Prediction Dataset

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:19:28.499487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a7d99f9-27d2-4029-a2cc-a5b7cce84c0b · inbound

Generative AI for Autonomous Driving: A Review cites this paper.

Generative AI for Autonomous Driving: A Review One Thousand and One Hours: Self-driving Motion Prediction Dataset

Reference 266

Resolution: unresolved; no resolver link, observed 2026-08-07T15:24:07.392221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33f9032f-4305-4a8c-991e-093475876969 · inbound

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources cites this paper.

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources One Thousand and One Hours: Self-driving Motion Prediction Dataset

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T06:50:19.379655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.