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Paper Citation Record · LEDGER

Parting with Misconceptions about Learning-based Vehicle Motion Planning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 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 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:17:27.216699Z

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

source=pdf_text observed=2026-05-15T15:05:31.928650Z digest=sha256:415e71df55d799df90eb8693e291ca2d1fae72d8c12231675f9e03d07d41a707

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.

source=pdf_text observed=2026-08-11T18:16:00.375423Z digest=sha256:cb8ee692d77a8470383115a2e31186253b152084f67351bea9769d79c8439ca6

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.

source=arxiv_source observed=2026-08-10T16:51:27.652900Z digest=sha256:b6fcb22ceb0a7062d9ed7eb71b7617287b702ef9383ad909cba4248421c7fe6e

Observation 0922d2dd-c59f-4eba-9eee-bfee2a96f501 · inbound

Inferring Driving Maps by Deep Learning-based Trail Map Extraction cites this paper.

Inferring Driving Maps by Deep Learning-based Trail Map Extraction Parting with Misconceptions about Learning-based Vehicle Motion Planning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T21:17:27.216699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:17:27.216699Z digest=sha256:020f1c8be9440931fd5ac2e8b7bde22b2ff34379f1cfd338dc37d62b736ff354

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.

source=pdf_text observed=2026-08-07T15:24:07.357724Z digest=sha256:153a761361d30fbc82df317fdd3c1263044ede198c23748e95d6d74100b0cc66

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

source=pdf_text observed=2026-05-22T13:18:30.486507Z digest=sha256:1a5ca312d51cf8a010adf4343cc8f96bd7a780732d3161d3a1ba714ed41ae21d

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.

source=pdf_text observed=2026-08-07T05:23:30.524769Z digest=sha256:877fd342e780b28b3cbd5e2e65ca665028d5bb6331e45bd0606428cf39fb093d

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

source=pdf_text observed=2026-05-09T20:55:26.571128Z digest=sha256:8ac932285c7fcdd653d74cfc6afc8021a63294268f356afae6c0df3542b1e7b7

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

source=pdf_text observed=2026-05-14T20:44:08.091470Z digest=sha256:7468ba1820aa690ff00a77668da943b5a92ea1b2c451a7fbad8a75d5abea106c