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Paper Citation Record · LEDGER

Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2405.15324.

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

pith.paper-citation-record.v1
2405.15324 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 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:25:46.106092Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T08:47:01.939849Z

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 9da65af0-7b88-4cd2-8f43-9fc8818581ea · 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 Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T22:25:46.106092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:25:46.106092Z digest=sha256:125b66aac9fd20cba4550c03834a929ba53c20de9e3f32c87f66cda85ae3e099

Observation 725eb47e-cb08-4a10-981d-25af9d6245b4 · inbound

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects cites this paper.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:55.273259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:55.273259Z digest=sha256:be7a03c90ac3689e388f9d81b914e5c450a92c400e5881d7a5d400580835087f

Observation ff3516a6-1ea5-4afa-a0c7-908697ad1d90 · inbound

CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving cites this paper.

CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T13:47:14.139184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:47:14.139184Z digest=sha256:d21ca4456bf72e590c40282c6a90c608715e0f8b7a31b3e1ed4864c28918ccd8

Observation 4448f754-01a2-4b35-8c2e-7c43e7b4fb74 · inbound

Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving cites this paper.

Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:20:50.446762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T00:16:35.823270Z digest=sha256:faee4115cfd1eadbd94cbd0d2dab3afe9d195d2b905a0a1fafdd0ceb43ecce92

Observation 1ec33b50-ede3-45f7-a0bb-db23a2fe0d2f · inbound

A Survey on Vision-Language-Action Models for Autonomous Driving cites this paper.

A Survey on Vision-Language-Action Models for Autonomous Driving Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-06T21:31:04.633849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:31:04.633849Z digest=sha256:34277a9ba812e269e30ddfbe4a61a08a5188c9e2d7c92a671c9d5e974fab096e

Observation 4e0b1168-1426-49dc-beff-514af133630b · inbound

CogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinking cites this paper.

CogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinking Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T17:18:27.447550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:18:27.447550Z digest=sha256:590412a91440675d972a5a193726052c9faaf98cc66ca6e8d71772f7aa261090

Observation 2c570247-09f4-49ad-a390-34c4fbbd9ed3 · inbound

SAGE-Nav: Leveraging LLM Planning and Alignment Fusion for Hierarchical Scene Graph-Guided Navigation cites this paper.

SAGE-Nav: Leveraging LLM Planning and Alignment Fusion for Hierarchical Scene Graph-Guided Navigation Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-04T19:20:06.901510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-25T21:28:01.593510Z digest=sha256:cfb05b2e5889a7a0be1cb20eeb48c17084e571385de062a6914a47b9c137aed5

Observation 87681913-233e-426e-b454-84472a113780 · inbound

FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation cites this paper.

FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 31

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T08:47:01.941525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-10T08:45:46.406210Z digest=sha256:84a9c6e86e98e69afbc5f6a13e78cc93543df15090a36b7bfc9a22402b976a54