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Paper Citation Record · LEDGER

A Review of Safe Reinforcement Learning: Methods, Theory and Applications

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2205.10330.

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

pith.paper-citation-record.v1
2205.10330 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 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 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:03:17.886563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:13:53.357631Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0bf72d01-6c78-4550-8d59-77336c8f6209 · inbound

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control cites this paper.

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 17

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no resolver link, observed 2026-08-09T13:03:17.886563Z

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Unavailable: canonical work link unavailable.

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Observation c7a6292d-cbc7-42ba-a476-38ad1ea73534 · inbound

Polynomial-Time Approximability of Constrained Reinforcement Learning cites this paper.

Polynomial-Time Approximability of Constrained Reinforcement Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 19

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source=pdf_text observed=2026-08-08T11:45:35.640679Z digest=sha256:76aa4cc25b2f91eb8b4ef8d9befe48395fa786a22b0005d554881d537fd20cfe

Observation 0e7ef777-33c8-4ce3-9e4b-c3910318b4b4 · inbound

SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning cites this paper.

SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 56

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arxiv_id, observed 2026-05-23T01:32:22.511123Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation cd92cda9-e161-4f1d-9247-3f3d6251f600 · inbound

Addressing Moral Uncertainty using Large Language Models for Ethical Decision-Making cites this paper.

Addressing Moral Uncertainty using Large Language Models for Ethical Decision-Making A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 39

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arxiv_id, observed 2026-05-23T03:02:27.022470Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T02:59:59.917462Z digest=sha256:1025e9561af1c0997248f51e9cbf8147f11c8a976ffa0862c0f2437dc637221b

Observation dd28ad47-5f5d-446c-9af6-b2b9d975e6f5 · inbound

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving cites this paper.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 3

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source=pdf_text observed=2026-08-07T15:13:38.190951Z digest=sha256:7fc5f55d074805c760ab85303f7fa98787886d4367a0715b95f60b3f1dab5b24

Observation 4720fc79-0604-4f11-8fca-7d0a01f03ca0 · inbound

Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning cites this paper.

Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 23

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source=arxiv_source observed=2026-08-07T13:58:11.528104Z digest=sha256:0dfad7e01cefa3761b236428fe5af807ef0b09a28bf8286bba2fe523ad1eda4d

Observation 0d6cb76d-128d-48dc-990e-0fad61852665 · inbound

SafeOR-Gym: A Benchmark Suite for Safe Reinforcement Learning Algorithms on Practical Operations Research Problems cites this paper.

SafeOR-Gym: A Benchmark Suite for Safe Reinforcement Learning Algorithms on Practical Operations Research Problems A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 8

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source=pdf_text observed=2026-08-07T11:32:01.311859Z digest=sha256:0089390009d07d2e3fdb59b59a27daa7f7f9e09143a601cc662ff07f50ef1cfb

Observation 6c8fa168-2129-44b3-88b2-720865288466 · inbound

Safe Planning and Policy Optimization via World Model Learning cites this paper.

Safe Planning and Policy Optimization via World Model Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 9

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source=pdf_text observed=2026-08-07T10:38:20.430333Z digest=sha256:955528220264244a388016aae96043bf7a51ba2acf4ec3714c214684d6f7b2bc

Observation f6f8ac98-85ba-4bfc-982c-2837f6a708bc · inbound

Online Learning Control Strategies for Industrial Processes with Application for Loosening and Conditioning cites this paper.

Online Learning Control Strategies for Industrial Processes with Application for Loosening and Conditioning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 19

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source=pdf_text observed=2026-08-07T05:03:03.922702Z digest=sha256:13b4e614098db064693f30067b6643b4dd494114f586a40d0272713c7b08c95d

Observation 09a248d6-fb45-4bf9-bb6f-fdd6f58333e2 · inbound

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact cites this paper.

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 264

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Observation 11fa7e59-32c5-40c5-ba11-5618b2dcd1be · inbound

Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies cites this paper.

Closed-Form Robustness Bounds for Second-Order Pruning of Neural Controller Policies A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 6

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Observation ad4d0621-b059-413d-ba5f-73b60461ee9c · inbound

Optimistic Exploration for Risk-Averse Constrained Reinforcement Learning cites this paper.

Optimistic Exploration for Risk-Averse Constrained Reinforcement Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 18

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source=pdf_text observed=2026-08-06T18:16:20.319931Z digest=sha256:d5be35e94176baea27f81a2065383f586eb54d2f2109045cd304f1750930dc3c

Observation 6d5ebb4b-2f56-4c4c-a0b4-c539cb611fa1 · inbound

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review cites this paper.

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 51

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Observation e7955322-735e-4a0f-8da2-cfe62c31fec5 · inbound

End-to-End Humanoid Robot Safe and Comfortable Locomotion Policy cites this paper.

End-to-End Humanoid Robot Safe and Comfortable Locomotion Policy A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 27

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Observation e30d4525-03d8-4250-a809-93b09f70bd28 · inbound

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions cites this paper.

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 42

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arxiv_id, observed 2026-05-18T22:41:53.839548Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T22:37:32.388931Z digest=sha256:131119cac57ed480a0d9c2b1e0973e428f8ddd0cd3fdedba3230bf5d09ad1c28

Observation 7384d603-4702-4eac-ab1f-8a2cce5348fa · inbound

Constrained Decoding for Safe Robot Navigation Foundation Models cites this paper.

Constrained Decoding for Safe Robot Navigation Foundation Models A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 32

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arxiv_id, observed 2026-05-18T19:11:47.450231Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0546dd58-1a88-4fa5-8ce0-c78e6cfdbac0 · inbound

The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification cites this paper.

The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 23

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arxiv_id, observed 2026-05-18T10:31:14.918174Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 01cb3e5b-e3c4-46fd-864a-be1e7fc96127 · inbound

Data-Driven Synthesis of Probabilistic Controlled Invariant Sets for Linear MDPs cites this paper.

Data-Driven Synthesis of Probabilistic Controlled Invariant Sets for Linear MDPs A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 3

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arxiv_id, observed 2026-05-13T20:08:13.116164Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation daa9f1eb-efa6-48a0-8914-230f31fb0c9c · inbound

Safe and Policy-Compliant Multi-Agent Orchestration for Enterprise AI cites this paper.

Safe and Policy-Compliant Multi-Agent Orchestration for Enterprise AI A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 3

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arxiv_id, observed 2026-05-10T06:46:37.334147Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T06:42:57.319962Z digest=sha256:f8bf9baa1b9e017e937bb008b43db2c22abea374c1c8b82877ac84ba5f4ced44

Observation b39aad05-ae4b-438e-a82b-3dc8a40481e9 · inbound

Learning Control Policies to Provably Satisfy Hard Affine Constraints for Black-Box Hybrid Dynamical Systems cites this paper.

Learning Control Policies to Provably Satisfy Hard Affine Constraints for Black-Box Hybrid Dynamical Systems A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 26

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arxiv_id, observed 2026-05-11T19:36:13.090999Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8cc66a4a-7e89-45b3-9229-08d90494eaf7 · inbound

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning cites this paper.

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 8

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arxiv_id, observed 2026-05-12T10:26:29.254565Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0d8300f2-8bab-48e2-8947-c09ccf4297dc · 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 Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 6

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arxiv_id, observed 2026-05-20T21:49:05.138755Z

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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:a3ba7bb95502d2c7310a6a291fc21b9248cda5139f90459c0bc12295faca3099

Observation e385ecf4-4da5-4b10-8ae9-717027c3d98c · 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 Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 6

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arxiv_id, observed 2026-05-20T21:39:03.469594Z

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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=sha256:1df0bb8825ee041f9669243796c7a3269fec69295182f0bde7a332909cbcda45

Observation 016af7b0-4758-45d8-949a-520f9247e3e7 · inbound

Regularized Reward-Punishment Reinforcement Learning cites this paper.

Regularized Reward-Punishment Reinforcement Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 37

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arxiv_id, observed 2026-06-29T19:13:53.359054Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 760398c0-5514-4ab2-bf6d-0123d24aeaec · 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 Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 6

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