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Paper Citation Record · LEDGER

The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2308.05731.

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

pith.paper-citation-record.v1
2308.05731 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:38:30.583889Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:21:35.787241Z

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 a3d06157-4f5e-42ff-a06d-b424cca2ad56 · inbound

Integrating Decision-Making Into Differentiable Optimization Guided Learning for End-to-End Planning of Autonomous Vehicles cites this paper.

Integrating Decision-Making Into Differentiable Optimization Guided Learning for End-to-End Planning of Autonomous Vehicles The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T04:38:30.583889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:38:30.583889Z digest=sha256:222d4aca40953b1422dfef755ba0ab666ebe63925b4d210df9e02a8953a2d85c

Observation 108c338a-f060-4067-81b4-db1aa0659339 · 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 The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T16:51:27.670051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:51:27.670051Z digest=sha256:70f3a05209e86d28aa0cdcafeb4ef107fb504e3ed52c4d9edd7ec48498094d66

Observation 5cc831f6-7102-4b34-ba40-eb6a49374d9e · inbound

Dream to Drive with Predictive Individual World Model cites this paper.

Dream to Drive with Predictive Individual World Model The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T11:08:53.090627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T11:08:53.090627Z digest=sha256:8e2caa9abd9dec746d91a9c020259d4482f91e39af920ca3681514dcfef33483

Observation 489effbf-3ab3-4c88-9f10-a874c2e3e289 · inbound

Knowledge Integration Strategies in Autonomous Vehicle Prediction and Planning: A Comprehensive Survey cites this paper.

Knowledge Integration Strategies in Autonomous Vehicle Prediction and Planning: A Comprehensive Survey The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T20:44:01.548637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:44:01.548637Z digest=sha256:cf565e4629fcba25c7febb9cd8d32ff96452de8fd7eda0560e6b7f10f0a3e008

Observation 8dbd5e28-4cc1-42df-af33-457085c03701 · 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 The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:21:35.790300Z

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.

source=pdf_text observed=2026-05-22T13:18:30.486507Z digest=sha256:24a63e8bced45744347b5fa4545c1b20c572501415c247932c598674dfc4a32d