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Paper Citation Record · LEDGER

Off-Policy Primal-Dual Safe Reinforcement Learning

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.14758.

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

pith.paper-citation-record.v1
2401.14758 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T05:32:04.237084Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:33:58.556671Z

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 9d0ad8ed-6e32-4fcb-b826-9748be050b13 · inbound

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models? cites this paper.

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models? Off-Policy Primal-Dual Safe Reinforcement Learning

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:57:33.119515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T07:55:31.706717Z digest=sha256:bc70201bf59e8a14081c9d357b2ab6d453e9992885627b21bda9034f2485948d

Observation 0e68b6d8-03f4-484f-b19c-15736431ce3b · inbound

PREFINE: Preference-Based Implicit Reward and Cost Fine-Tuning for Safety Alignment cites this paper.

PREFINE: Preference-Based Implicit Reward and Cost Fine-Tuning for Safety Alignment Off-Policy Primal-Dual Safe Reinforcement Learning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:33:58.558598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-21T05:32:04.237084Z digest=sha256:becb4015ac42a5fecf034a8f8211db793b63342aab12ca0cdc22237147e618c9