Paper Citation Record · LEDGER

Large Trajectory Models are Scalable Motion Predictors and Planners

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2310.19620.

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

pith.paper-citation-record.v1
2310.19620 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:18:48.197173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T06:48:01.093709Z

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 c056c5b9-7528-4221-83ea-b0992dac6401 · inbound

DriveGPT: Scaling Autoregressive Behavior Models for Driving cites this paper.

DriveGPT: Scaling Autoregressive Behavior Models for Driving Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:48.197173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3886fe16-a26b-4ffe-829b-19b160cb3e0e · inbound

Diffusion-Based Planning for Autonomous Driving with Flexible Guidance cites this paper.

Diffusion-Based Planning for Autonomous Driving with Flexible Guidance Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T14:15:08.647714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5d68802-99a3-4efe-8d22-5591548b1570 · inbound

Motion Forecasting for Autonomous Vehicles: A Survey cites this paper.

Motion Forecasting for Autonomous Vehicles: A Survey Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T15:54:34.177273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77a1c663-b7d6-4e8f-bf6e-998060f20143 · inbound

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

Generative AI for Autonomous Driving: A Review Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 173

Resolution: unresolved; no resolver link, observed 2026-08-07T15:24:06.906960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8d40546-da2f-49f0-afb5-52d6040ccebb · inbound

Autoregressive Meta-Actions for Unified Controllable Trajectory Generation cites this paper.

Autoregressive Meta-Actions for Unified Controllable Trajectory Generation Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:49.069135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9286cce4-acda-46c7-8abc-ef9d952d5960 · inbound

RoCA: Robust Cross-Domain End-to-End Autonomous Driving cites this paper.

RoCA: Robust Cross-Domain End-to-End Autonomous Driving Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T04:40:59.652702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 285fe604-2551-4266-9c82-8cca7977bfc9 · inbound

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving cites this paper.

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-17T06:48:01.096293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 02d20eb9-5c0e-4e2e-80c4-12eb2bc818e2 · inbound

World Models as Adversaries: Multi-Agent Self-Play Fine-Tuning for Robust Motion Planning cites this paper.

World Models as Adversaries: Multi-Agent Self-Play Fine-Tuning for Robust Motion Planning Large Trajectory Models are Scalable Motion Predictors and Planners

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-14T10:22:08.922396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.