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Paper Citation Record · LEDGER

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2206.04436.

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

pith.paper-citation-record.v1
2206.04436 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 2026-08-14T06:32:32.682623+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:21:18.453588Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T18:23:51.471687Z

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 6ba8d291-d21f-4541-8de4-667a1bc26e33 · inbound

Exploratory Diffusion Model for Unsupervised Reinforcement Learning cites this paper.

Exploratory Diffusion Model for Unsupervised Reinforcement Learning Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-08T13:21:18.453588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:21:18.453588Z digest=sha256:7a911664fcfa2095ead8bab3f7e25243cc9e6802c65e544a8e85bbaa92f5dc77

Observation dc94ecf2-b14e-4606-9da9-7e38a8cbf109 · inbound

Safe-Support Q-Learning: Learning without Unsafe Exploration cites this paper.

Safe-Support Q-Learning: Learning without Unsafe Exploration Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:36:38.384687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-07T16:36:35.746034Z digest=sha256:a890dc671213a1ebc60afbfa8e4920a265a9985bf09de3c0f85494580f310f82

Observation 1c3b1850-98a9-4cf8-925e-9adbab47625c · inbound

Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning cites this paper.

Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:32:30.558232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T07:28:24.455817Z digest=sha256:daae86e693340a2aac031280da48aa41de466794e4f2329d709d6279bb4a0fc0

Observation 5cbfbc4c-9f0e-48d4-85e7-a1569461087c · inbound

Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning cites this paper.

Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:49:10.087416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T22:48:55.661356Z digest=sha256:073a6152308825d4d929dc3d31481953212e70bfacea037df86acc87dd6bfc57

Observation a71f6cd2-6674-455f-8347-ecfe90e2629e · inbound

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning cites this paper.

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:49:05.114084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-20T21:48:43.143169Z digest=sha256:4677507726247be84851e9993329980e9f92b465a97482c3d2288d77cd8ad7d4

Observation 05e9885e-4538-479d-b2e2-a0d16cc6e6ca · inbound

Safe Continual Reinforcement Learning under Nonstationarity via Adaptive Safety Constraints cites this paper.

Safe Continual Reinforcement Learning under Nonstationarity via Adaptive Safety Constraints Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:39:03.494657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-20T21:36:33.206033Z digest=sha256:ce2f311162a105d8081fd1eed4ea11dea6b08f76b0b84ac7fc0f6822de45ec57

Observation e17d63f0-0f87-4ffb-be31-d327e799068b · inbound

RS-Diffuser: Risk-Sensitive Diffusion Planning with Distributional Value Guidance cites this paper.

RS-Diffuser: Risk-Sensitive Diffusion Planning with Distributional Value Guidance Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-06-29T18:23:51.473150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T05:05:39.828659Z digest=sha256:f1707a0d9a64c3e7f7f04d620d0d398adcbe58b41c6b9273f69118af805edce2

Observation 22d283e7-d656-469e-95aa-2ca0173342cf · inbound

Adjustment Speed as a Safety Constraint for Nonstationary Reinforcement Learning cites this paper.

Adjustment Speed as a Safety Constraint for Nonstationary Reinforcement Learning Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-01T12:15:44.291124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:15:44.291124Z digest=sha256:0c5db9f193f0d3ee34d34ad38850d3b41c85bc342f741e2585e96c7b8689340e