Paper Citation Record · LEDGER

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks

As of 12 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2412.04153.

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

pith.paper-citation-record.v1
2412.04153 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:46:47.809846Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

verified exact1
verified fuzzy12
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fdf42074-223c-41fb-a76f-832d17f5d8e1 · outbound

This paper cites Constrained policy optimization.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Constrained policy optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.690685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b2f30b-af06-4c7e-a3e8-9753179948df · outbound

This paper cites Exploring under constraints with model-based actor-critic and safety filters.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Exploring under constraints with model-based actor-critic and safety filters

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.359758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 89dadc74-6225-4b55-801a-beac0ef708d4 · outbound

This paper cites Control barrier functions: Theory and applications.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Control barrier functions: Theory and applications

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.341772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 475acf9e-724e-4b35-9435-cb3c320cfc67 · outbound

This paper cites o m and Tore H \.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks o m and Tore H \

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.325928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8de02ea4-4d5e-4a3b-a7ee-0444ed7ae8ea · outbound

This paper cites Where to go next: learning a subgoal recommendation policy for navigation in dynamic environments.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Where to go next: learning a subgoal recommendation policy for navigation in dynamic environments

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.310211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d159a33d-9900-4d2e-bb6a-7eca0da27359 · outbound

This paper cites Safe reinforcement learning via shielding under partial observability.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Safe reinforcement learning via shielding under partial observability

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.293847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 35afc550-2d84-41b9-b92c-fe203bd8da85 · outbound

This paper cites Pybullet, a python module for physics simulation for games, robotics and machine learning.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Pybullet, a python module for physics simulation for games, robotics and machine learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.277268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 17b2177e-567d-45b3-aafc-e8d564f39a66 · outbound

This paper cites Safe Exploration in Continuous Action Spaces.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Safe Exploration in Continuous Action Spaces

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.730387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db2338fe-5da7-4bb3-8f2e-fe10f3635950 · outbound

This paper cites Safe multi-agent reinforcement learning for behavior-based cooperative navigation.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Safe multi-agent reinforcement learning for behavior-based cooperative navigation

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-11T21:46:48.110539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e78072dd-f704-4be9-8797-e452200db7d1 · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.740847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e25fbf4-1c99-4956-a469-a5eb116a5f8f · outbound

This paper cites Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.746141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e576be2f-df30-48da-a4f2-c6ef8a46f042 · outbound

This paper cites SafeDreamer: Safe Reinforcement Learning with World Models.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks SafeDreamer: Safe Reinforcement Learning with World Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.751481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb1ef198-49d5-49f5-b475-be205d3957ff · outbound

This paper cites OmniSafe: An Infrastructure for Accelerating Safe Reinforcement Learning Research.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks OmniSafe: An Infrastructure for Accelerating Safe Reinforcement Learning Research

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.756731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 601e906b-7322-4f7b-b574-398969d00804 · outbound

This paper cites Benchmarking Batch Deep Reinforcement Learning Algorithms.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Benchmarking Batch Deep Reinforcement Learning Algorithms

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.761953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63d412ca-88d1-4863-bba3-e29ff6fe59af · outbound

This paper cites Saut \'e rl: Almost surely safe reinforcement learning using state augmentation.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Saut \'e rl: Almost surely safe reinforcement learning using state augmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.250696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c744c90c-486e-4f35-af90-783531fffb19 · outbound

This paper cites Responsive safety in reinforcement learning by pid lagrangian methods.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Responsive safety in reinforcement learning by pid lagrangian methods

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.772428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6864f15d-b65f-438b-9e96-6555df89dc23 · outbound

This paper cites Reward Constrained Policy Optimization.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Reward Constrained Policy Optimization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.777452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09b25504-6a5c-4ab0-8408-c429518b6700 · outbound

This paper cites Recovery rl: Safe reinforcement learning with learned recovery zones.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Recovery rl: Safe reinforcement learning with learned recovery zones

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.223145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 04d10399-31f3-4457-b233-67bfba3530fa · outbound

This paper cites Probabilistic model predictive safety certification for learning-based control.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Probabilistic model predictive safety certification for learning-based control

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.206780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ce486482-9077-42d9-a849-e8c74d333747 · outbound

This paper cites A predictive safety filter for learning-based control of constrained nonlinear dynamical systems.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks A predictive safety filter for learning-based control of constrained nonlinear dynamical systems

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.190864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 36dda262-eca5-4f18-8bed-3af90bd56238 · outbound

This paper cites Benchmarking reinforcement learning techniques for autonomous navigation.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Benchmarking reinforcement learning techniques for autonomous navigation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.174087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b9854771-a858-46b6-8fd8-74d130a7f4f4 · outbound

This paper cites MAMPS: Safe Multi-Agent Reinforcement Learning via Model Predictive Shielding.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks MAMPS: Safe Multi-Agent Reinforcement Learning via Model Predictive Shielding

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T21:46:47.804510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff8352ce-f7f7-4d3c-ab4f-c6ba8ba554e6 · outbound

This paper cites Spatial-temporal-aware safe multi-agent reinforcement learning of connected autonomous vehicles in challenging scenarios.

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Spatial-temporal-aware safe multi-agent reinforcement learning of connected autonomous vehicles in challenging scenarios

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:46:48.157922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.