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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:f1db8bac1bbd6ae9e61b8dd12ac31f50ca095bd14f7d6002311e45d8a2ef9683

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=sha256:5c9705b0a352660af20236715f4cb7cae0f23e77803ee4c02bcf87ad1e7d649d

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=sha256:2c7d647d6882d6381669d652891f8f636689edf4152e574b8481d7515d013cd9

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:ae1dd950ca04bc22827dc79612fcef4abd94d3da1637e637e8f42b15803c2f2f

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=sha256:8aa771e9b891164590c27487a1abe8dae6002f4d0ee3b20b6d84b3e1c1124611

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:adea2a8f43e5b20c4a5c005efcd6f6a1ef79f15e7bce2cac5e06564d697b3134

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:fdf2ae41c3e2cc38489ebb843a0eea33fa2cd544487e30402375f0f42f080466

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:ede401514e3191e9b8b245e66be82f00c0d7f964736651ab00212fb03811a95f