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Paper Citation Record · LEDGER

Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2206.01558.

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

pith.paper-citation-record.v1
2206.01558 v1

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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:59:06.385820Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:59:19.931095Z

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 728a8fb2-4c7f-4286-858c-987f2b8e97d2 · inbound

Uncertainty Prioritized Experience Replay cites this paper.

Uncertainty Prioritized Experience Replay Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T04:59:06.385820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:59:06.385820Z digest=sha256:01423b052373ec250aca88752131c7f743d9209c673df2c58fc08069e2edfe1a

Observation 941e3176-5522-4b1d-aa8a-c91731d50bd6 · inbound

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation cites this paper.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-06T19:19:29.451527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.451527Z digest=sha256:97bb5fe59fc838c344ede01ca4fa728a9526d7eab86010f554babaef1b1a037b

Observation ff375af6-5a28-49d1-af80-ca173930e1b0 · inbound

Epistemic Uncertainty for Test-Time Discovery cites this paper.

Epistemic Uncertainty for Test-Time Discovery Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:57:06.174278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T01:52:41.192353Z digest=sha256:11792863f88ccb9876c5ccd19ee3ed0c313f24012a0daa912f9ae43886001a47

Observation b9da2366-4a7b-4ac8-aabf-68692c8a23a1 · inbound

On the QUEST for Uncertainty Quantification via Highest Density Regions cites this paper.

On the QUEST for Uncertainty Quantification via Highest Density Regions Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:59:19.935177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T20:50:20.633948Z digest=sha256:d34d1d68fec5b38ba36405849da22c83480e6f770b77e06ab65a28583b1c07a6

Observation e8f4e2fa-ba1f-4f80-8d62-56ce881b50da · inbound

Auditing the Risk Claims of Distributional Reinforcement Learning cites this paper.

Auditing the Risk Claims of Distributional Reinforcement Learning Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Reference 65

Resolution
unresolved
no resolver link, observed 2026-07-14T04:26:46.686445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T04:26:46.686445Z digest=sha256:bd83a7d6b2700019adf86e8596a2b9e3100597246c99270a5a39c09a5377612f