Paper Citation Record · LEDGER

A Survey of Constraint Formulations in Safe Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2402.02025.

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

pith.paper-citation-record.v1
2402.02025 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:07:20.946727Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T18:03:47.876016Z

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 63d80279-eab4-4b46-9c77-8c9549ea32b3 · inbound

Vision-Language-Action Safety: Threats, Challenges, Evaluations, and Mechanisms cites this paper.

Vision-Language-Action Safety: Threats, Challenges, Evaluations, and Mechanisms A Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 69

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:21:10.610357Z

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.

Observation 767f3ad2-b1a2-408c-a0ce-848dda4d1fba · inbound

A Production-Ready RL Framework for Personalized Utility Tuning with Pareto Sweeping in Pinterest Recommender Systems cites this paper.

A Production-Ready RL Framework for Personalized Utility Tuning with Pareto Sweeping in Pinterest Recommender Systems A Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:49:15.083871Z

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.

Observation e0e71e40-0621-4489-bd8f-1eca630c09a9 · 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 Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-20T21:49:05.129364Z

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.

Observation 34839c64-92a4-4981-b39c-d2064ffd9e14 · 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 Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-20T21:39:03.491422Z

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.

Observation 633b528b-47a3-434b-9bb6-8af44e840e21 · inbound

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment cites this paper.

Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment A Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T18:03:47.877433Z

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.

Observation 6dff0780-35bf-4f90-b4be-263e2439b5af · 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 Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T12:15:40.588353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5c8db99-4b75-4016-aa4b-6512e73b5a51 · inbound

From Network Automation to Trustworthy Autonomous Networking in the LLM Era: A Network Control Intelligence Perspective cites this paper.

From Network Automation to Trustworthy Autonomous Networking in the LLM Era: A Network Control Intelligence Perspective A Survey of Constraint Formulations in Safe Reinforcement Learning

Reference 215

Resolution: unresolved; no resolver link, observed 2026-08-06T00:07:20.946727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.