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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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=sha256:49773ab2997d34ee30f4cfb042ba3f282ba18bbda295d30cb76b314be5db693b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T16:36:35.746034Z digest=sha256:6bd3693a3282b0045cf32155480e010b00ac09b9d2fb713be9a6bc24cd38bdb8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T07:28:24.455817Z digest=sha256:1c80b9fb95b1772bee178929d79397a9f28de02825fe35c6b3e572a62f8478cd

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T22:48:55.661356Z digest=sha256:a9d397c62254563d155a8dca233732861470941e3907db894d38df18c4b0b457

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T21:48:43.143169Z digest=sha256:f8fdd612a07ad944879a6c97444871614864c2d5e8c99e175e3fa2621bf2ec6e

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T21:36:33.206033Z digest=sha256:f9c332bc66e87b227daec4fdb07ab029b9bc809f88dd1c5342e8ef42a4ce66a9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T05:05:39.828659Z digest=sha256:770903766e4ca1b7773da22ae7a114915dabc3fd433f92f533357266a9680a9b

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:fa77ec702b9e978bd4fd0f9c8ea509ac286a92234d2eb59e9051726ca9a27c45