Paper Citation Record · LEDGER

Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1802.06480.

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

pith.paper-citation-record.v1
1802.06480 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:09:54.765869Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

43
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e99eb0bb-abff-4441-8cd7-6ac7fc9bdca2 · inbound

Effective Reward Specification in Deep Reinforcement Learning cites this paper.

Effective Reward Specification in Deep Reinforcement Learning Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

Reference 192

Resolution: unresolved; no resolver link, observed 2026-08-11T19:09:54.765869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c2c0def-25b7-438f-bb8c-16f8304b8d18 · inbound

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning cites this paper.

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T13:25:20.457721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f1d205e-0fd2-4481-bc3e-a208e4e89b08 · inbound

PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning cites this paper.

PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T21:20:29.441050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6feb0acf-3df2-4dc7-94f5-408ca55f97ae · inbound

Control Synthesis with Reinforcement Learning: A Modeling Perspective cites this paper.

Control Synthesis with Reinforcement Learning: A Modeling Perspective Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T07:37:43.121038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a7d1de5-8c22-4381-af1b-dfa260f81a71 · inbound

Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics cites this paper.

Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-29T08:43:14.641498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a1c9b681-888b-4615-b2ae-46af5d884d8f · inbound

Stationary Robust Mean-Field Games under Model Mismatches cites this paper.

Stationary Robust Mean-Field Games under Model Mismatches Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

Reference 163

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T08:49:42.810841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.