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Paper Citation Record · LEDGER

Exploring applications of deep reinforcement learning for real-world autonomous driving systems

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1901.01536.

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

pith.paper-citation-record.v1
1901.01536 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:41:09.483807Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T16:49:57.153845Z

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 4095730d-ef4c-4ba9-89aa-bb9c06c20844 · inbound

Learning Isometric Embeddings of Road Networks using Multidimensional Scaling cites this paper.

Learning Isometric Embeddings of Road Networks using Multidimensional Scaling Exploring applications of deep reinforcement learning for real-world autonomous driving systems

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T10:41:09.483807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:41:09.483807Z digest=sha256:c0c9c55d2b97e7b382b25c9091d1eed3f8402aad4e99ef9cf2a17c607a02b262

Observation 62d8326f-6f79-465a-9a07-7bd997964d37 · inbound

Uncertainty-aware reinforcement learning for chemical language models cites this paper.

Uncertainty-aware reinforcement learning for chemical language models Exploring applications of deep reinforcement learning for real-world autonomous driving systems

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-07-04T16:49:57.155057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-26T00:18:03.416401Z digest=sha256:422a91e2a2303fc04f6d4863d568f47d9ae0691a9422e1f10323b059667ba179