Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 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 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:13:38.190951Z

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

  • 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 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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T01:27:33.123243Z digest=sha256:497de08f9ec80793bdc48723bd27be6c30901903e3a54e317dc4ad4e2d705f0b

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T02:59:59.917462Z digest=sha256:b1bf442daa4383f13a15967acf4e7ba2c64a3fd96b86b4d054fc6dda611d7cfe

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

Resolution
unresolved
no resolver link, observed 2026-08-07T15:13:38.190951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:13:38.190951Z digest=sha256:84fa5fc6c40a73cf74c3cb0286a87742d659f6c7325bc329c3d243c31563106d

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

Resolution
unresolved
no resolver link, observed 2026-08-07T13:58:11.528104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:58:11.528104Z digest=sha256:2cd98eb4167c32a99de108eaf32dcccab9c9a643b154645793640115de8150b6

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

Resolution
unresolved
no resolver link, observed 2026-08-07T11:32:01.311859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
unresolved
no resolver link, observed 2026-08-07T10:38:20.430333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:38:20.430333Z digest=sha256:66b25c843419716825f3c024cda3bd8e416b83c45c346e36cf936d0deeb63a8e

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

Resolution
unresolved
no resolver link, observed 2026-08-07T05:03:03.922702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
unresolved
no resolver link, observed 2026-08-06T21:07:11.562147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:07:11.562147Z digest=sha256:9b483a80645df2489a3033ae159fec8bf130ff826c6f1f20160dc33ae9412571

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

Resolution
unresolved
no resolver link, observed 2026-08-06T21:54:43.614688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:54:43.614688Z digest=sha256:6f1b38dc60416b3d4c33f96875496d7716f4a4df7041c44f09ba6302245c2dc4

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

Resolution
unresolved
no resolver link, observed 2026-08-06T18:16:20.319931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:16:20.319931Z digest=sha256:af41a1eeaed9af3db0b0f6192ef7bcad56a9b127b448c235c11801113699a62b

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

Resolution
unresolved
no resolver link, observed 2026-08-06T17:42:53.625181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:42:53.625181Z digest=sha256:39c1a40193e5932ac0c31d9cc0ce1fb5a0f132fb7a3915eb03f0e28b6a68cc39

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

Resolution
unresolved
no resolver link, observed 2026-08-05T22:05:09.471156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:05:09.471156Z digest=sha256:a1697d3d015b87670de4d78973eb6888813bcdcb5cc8313a624b58af4cf24c5a

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T22:37:32.388931Z digest=sha256:273d3290e16949cd0176a65b9474da07179f5508ca4bbdd6edb7d1d6857d931c

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T19:07:18.832187Z digest=sha256:fc8a24d76066b5ea8e5567b7bfed03e8ccb7fa680e1e12cf7f39850fafb4b2e2

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T10:27:40.188511Z digest=sha256:f5f2f3eb67d74fa55dd49d5475043dd4b0fd07791467521b8c8b1b1364c0a6e1

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T20:03:22.406198Z digest=sha256:0d70d64558dd298b506eed89803bd5b29e30365e9252cd6f5adc44cf85f3ee88

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T06:42:57.319962Z digest=sha256:6f05d11fe9fca1f98cb947256fe9da3f4e121156fcee9fee12c5d693a5102d38

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T11:36:39.916952Z digest=sha256:0aec64e3396e026db91a3c2bbff082868fd1091eb7aca59697ef4e8914558c5e

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T06:12:37.845017Z digest=sha256:c86589d5aaf5af4e26a96e5dba8c87238d3afeaa80319df7fa381d9592b2e656

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T21:48:43.143169Z digest=sha256:f4802fc116fbf0d428389ad5a2b08bd2f44fc609218290441ff4827ade61ea85

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T21:36:33.206033Z digest=sha256:4c25477aa4679910676b31754adeb1a90e9419bc7654c13f725c77db2b63dc26

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T04:49:28.330471Z digest=sha256:ba7b4c85df5ad02eed1aae85b8545d7e8921d8a64ddcfa24ecbb355b70b6eac4

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

Resolution
unresolved
no resolver link, observed 2026-08-01T12:15:37.928524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:15:37.928524Z digest=sha256:f47867f49033c102c3cb6167b26cbede1904b65bdd3308c27a1571e94d4accf4