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Paper Citation Record · LEDGER

Path Learning with Trajectory Advantage Regression

As of 21 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 1 inbound Pith citation observation for arXiv:2506.19375.

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

pith.paper-citation-record.v1
2506.19375 v1

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:45:12.921086Z

measured 7 of 7 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:52:30.579434Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T18:16:14.067578Z

Reference resolution

6 of 6 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e2b9a64a-5c44-4cb8-8271-5e2e1988bd93 · outbound

This paper cites Deep Reinforcement Learning in Autonomous Car Path Planning and Control: A Survey.

Path Learning with Trajectory Advantage Regression Deep Reinforcement Learning in Autonomous Car Path Planning and Control: A Survey

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T18:45:12.893516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:45:12.893516Z digest=sha256:8e0aedd846809b1264a5c06eaf57b31bab1c6a576a4c4b818a2067cea27fa48f

Observation 396b2bf6-8c69-4897-99a4-ce7c7ababe77 · outbound

This paper cites Trajectory regression on road networks.

Path Learning with Trajectory Advantage Regression Trajectory regression on road networks

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:45:13.030212Z

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=arxiv_source observed=2026-08-15T18:45:12.900144Z digest=sha256:dca5886c1587e3b8d5c17c40cc3b5c6f440088a8f332fa4135064aa23e32f31f

Observation fde59e99-b960-4f9d-a840-83b5a9a2e9fd · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Path Learning with Trajectory Advantage Regression Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T18:45:12.905318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:45:12.905318Z digest=sha256:3404a5265dbd6596cdfe2e7d76100a24d2415d797b1b6070b95700931e4ce0af

Observation b0d690a3-eadc-4d13-ac4d-835179c02ca9 · outbound

This paper cites Route planning under uncertainty: The canadian traveller problem.

Path Learning with Trajectory Advantage Regression Route planning under uncertainty: The canadian traveller problem

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:45:13.013764Z

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=arxiv_source observed=2026-08-15T18:45:12.910695Z digest=sha256:53aa09ea524528ce47a7ea2824e0569b0a41c76a6ec537dfa868426861f3f635

Observation 4b5eb5c2-55ac-4d6d-bcb5-9b85f4ba092c · outbound

This paper cites Markov decision processes: discrete stochastic dynamic programming.

Path Learning with Trajectory Advantage Regression Markov decision processes: discrete stochastic dynamic programming

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T18:45:12.916011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:45:12.916011Z digest=sha256:8280187eb365e777d5a419caa6b22b59cd7d069a1089ee9464689c5711d663a8

Observation 140dce04-a6c6-49a1-8e5f-b42c43e32dcc · outbound

This paper cites Reinforcement learning: An introduction , volume 1.

Path Learning with Trajectory Advantage Regression Reinforcement learning: An introduction , volume 1

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T18:45:12.921086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:45:12.921086Z digest=sha256:da41b7e7ff16c45b14e685098e4111364de6c6c0bb38e89226ab24bc93a7b450

Pith citing papers

Observation 1ff0286d-deb8-4928-82f8-7b68c8bea277 · inbound

Cross-Process Defect Attribution using Potential Loss Analysis cites this paper.

Cross-Process Defect Attribution using Potential Loss Analysis Path Learning with Trajectory Advantage Regression

Reference 2025

Resolution
verified exact
local_arxiv, observed 2026-08-15T17:52:30.662070Z

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=2026-08-15T17:52:30.579434Z digest=sha256:6c498665f8ab917f195d72c8e89ef40074f74a2677bd25e3a389d736056f73a9