Paper Citation Record · LEDGER

Parting with Misconceptions about Learning-based Vehicle Motion Planning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2306.07962.

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

pith.paper-citation-record.v1
2306.07962 v2

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 2026-08-14T06:32:32.682623+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:16:00.375423Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:21:35.719160Z

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 46b1bcca-99e4-490a-b48c-f1efa72bd160 · inbound

GPT-Driver: Learning to Drive with GPT cites this paper.

GPT-Driver: Learning to Drive with GPT Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T15:05:32.028910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 736fa120-412c-4a35-ad4e-b3a7f0b6f42b · inbound

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model cites this paper.

Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T18:16:00.375423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2bd0d34-e088-40cf-b6a1-5578a1efb8a8 · inbound

Int2Planner: An Intention-based Multi-modal Motion Planner for Integrated Prediction and Planning cites this paper.

Int2Planner: An Intention-based Multi-modal Motion Planner for Integrated Prediction and Planning Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:27.652900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b946cc2a-1615-4be1-a745-e190938ba2ec · inbound

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

Generative AI for Autonomous Driving: A Review Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 259

Resolution: unresolved; no resolver link, observed 2026-08-07T15:24:07.357724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b1c4072-b706-40d5-90bb-92d7440ef9cb · inbound

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios cites this paper.

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:21:35.722576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3b467808-acd9-4a84-81d5-407fb95e016a · inbound

Scaling Laws of Motion Forecasting and Planning -- Technical Report cites this paper.

Scaling Laws of Motion Forecasting and Planning -- Technical Report Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-07T05:23:30.524769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6ba2308-b224-4df6-80c2-ee95ae3dc0e7 · inbound

Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive cites this paper.

Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:51:14.398598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7cdcdce0-8186-430b-a0d7-7bdcf8326b97 · inbound

Multistep Belief Space Dynamics Learning For Risk-Aware Control cites this paper.

Multistep Belief Space Dynamics Learning For Risk-Aware Control Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:47:58.988385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.