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Paper Citation Record · LEDGER

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2006.06091.

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

pith.paper-citation-record.v1
2006.06091 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 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:56:13.863081Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T14:55:48.556787Z

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 59a025fa-8224-4afa-9c2a-747ea85ea40a · inbound

LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks cites this paper.

LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T21:56:13.863081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:56:13.863081Z digest=sha256:59a9f1a44fd4e1dfe864ca5853e9c87fab7366a38c36ab1c4133cffd0e318110

Observation 6d95ad13-1518-4bca-9585-15e43102fd45 · inbound

Key Safety Design Overview in AI-driven Autonomous Vehicles cites this paper.

Key Safety Design Overview in AI-driven Autonomous Vehicles Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T17:32:13.355221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:32:13.355221Z digest=sha256:6d60a04a1a71f78a2a3f9f111f65ce89aac7f449943d682e5f27562f321cf072

Observation 4f74e34d-37f7-4cac-870d-2ed4094ccd37 · inbound

Mapping the Mind of an Instruction-based Image Editing using SMILE cites this paper.

Mapping the Mind of an Instruction-based Image Editing using SMILE Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T10:49:22.987354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:49:22.987354Z digest=sha256:9c4b9c03677e183b60e476df703ae73ab247c20f0f4249884dd5cf7cba4de33e

Observation 02309a32-ab49-4a42-8acb-6ade5f8d3090 · inbound

Application of Multimodal Large Language Models in Autonomous Driving cites this paper.

Application of Multimodal Large Language Models in Autonomous Driving Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T10:39:26.265804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:39:26.265804Z digest=sha256:afbc1bd2e740bfde2ccaeb2bcad5601a39abb153e8300bb77fd33060fc69ed3d

Observation 95cff8ad-5af7-4a83-99e9-570c3999be06 · inbound

Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization cites this paper.

Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-08T19:02:30.532686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:02:30.532686Z digest=sha256:47cb66c57cd269abfbb155dc6236754c61bb6333e837aed2a039fd0381c860d4

Observation 37975c13-9508-4fc5-91aa-95bea80c70f2 · inbound

LimSim Series: An Autonomous Driving Simulation Platform for Validation and Enhancement cites this paper.

LimSim Series: An Autonomous Driving Simulation Platform for Validation and Enhancement Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T22:25:46.081586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:25:46.081586Z digest=sha256:58830928d7414c1f9f06f858684e8cdfbdd208ca3b79bd33005c0250b8968e7a

Observation 049e273b-5ae1-4697-97ef-aab808ba9c84 · inbound

From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Driving cites this paper.

From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Driving Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:25.678027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:25.678027Z digest=sha256:4d9fb7b48a2092fa1b203a830750ced5a69ffad46d1e5a865db29f5e3249b944

Observation 4437feb6-392e-4e5c-9ca8-54e1663fdd62 · inbound

SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer cites this paper.

SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:55:48.560331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-05T14:55:48.241553Z digest=sha256:f873343eb9d4e94112392300193a84b3c5157cfda972a6562d341726d4e0f337