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Paper Citation Record · LEDGER

A CMDP-within-online framework for Meta-Safe Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.16601.

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

pith.paper-citation-record.v1
2405.16601 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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:47:45.346953Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T21:49:05.139995Z

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 f9b3a422-a687-4f61-846c-179424078cf5 · inbound

Estimation of Regions of Attraction for Nonlinear Systems via Coordinate-Transformed TS Models and Piecewise Quadratic Lyapunov Functions cites this paper.

Estimation of Regions of Attraction for Nonlinear Systems via Coordinate-Transformed TS Models and Piecewise Quadratic Lyapunov Functions A CMDP-within-online framework for Meta-Safe Reinforcement Learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:45.346953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:47:45.346953Z digest=sha256:00de563967eb24f2ce56dbfb4a26e695ceadbbd92fc198c0b631548f9278b6a0

Observation 066f69d3-43e6-475d-b152-70d3902125de · inbound

Why Does Agentic Safety Fail to Generalize Across Tasks? cites this paper.

Why Does Agentic Safety Fail to Generalize Across Tasks? A CMDP-within-online framework for Meta-Safe Reinforcement Learning

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:06:00.118999Z

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=2026-05-11T01:55:38.554161Z digest=sha256:d608c9b70823fb48c9ccdcc51687afad57217656f36e1163e5d977683ea2b59f

Observation f97b66d1-6563-4fed-96ae-be7e78e095e5 · 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 A CMDP-within-online framework for Meta-Safe Reinforcement Learning

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:49:05.141716Z

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=sha256:40ac9f10d8b7ff1d00b8d07e2fb7dce07b2a2b5de4d4c270ef691ce4c00023b9

Observation 81affb9c-25ff-4a26-80f5-da7fbaeeacce · inbound

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

Safe Continual Reinforcement Learning under Nonstationarity via Adaptive Safety Constraints A CMDP-within-online framework for Meta-Safe Reinforcement Learning

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:39:03.451451Z

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=sha256:034b09c1771230b9f4871fa43cf7dd94dd91f747c1bba7e25ca0a8908df3e89d

Observation 46f60b0f-f36d-4396-bb32-3494132bb77e · inbound

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

Adjustment Speed as a Safety Constraint for Nonstationary Reinforcement Learning A CMDP-within-online framework for Meta-Safe Reinforcement Learning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T12:15:40.078949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:15:40.078949Z digest=sha256:6651884ffecc6bfe85f324798f5e199b42765527a5c009241252a5dc78f8e163