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Paper Citation Record · LEDGER

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control

As of 10 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2510.20955.

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

pith.paper-citation-record.v1
2510.20955 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:23:18.766484Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

22 of 22 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d002d5ba-f0b3-45eb-b9c1-d28f76f2ab0a · outbound

This paper cites Sutton and Andrew G.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Sutton and Andrew G

Reference 1

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Observation e5679ba1-b9ca-4190-ad85-1b7305c34d1e · outbound

This paper cites Routledge, 1 edition, March 1999.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Routledge, 1 edition, March 1999

Reference 2

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Observation fa6f2bd6-f182-4ac9-bf2d-4d4cf721afc1 · outbound

This paper cites CONSERV ATIVE SAFETY CRITICS FOR EXPLORATION.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control CONSERV ATIVE SAFETY CRITICS FOR EXPLORATION

Reference 3

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Observation 8e12a26a-0b8f-4316-a43e-de9d1cb365ea · outbound

This paper cites Learning to be Safe: Deep RL with a Safety Critic.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Learning to be Safe: Deep RL with a Safety Critic

Reference 4

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Observation cf35bea8-2c67-4dfc-bef7-1fb15046095b · outbound

This paper cites When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning

Reference 5

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Observation 12c2574e-a244-494b-af2e-738480f6f563 · outbound

This paper cites Safe Exploration in Finite Markov Decision Processes with Gaussian Pro- cesses.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Safe Exploration in Finite Markov Decision Processes with Gaussian Pro- cesses

Reference 6

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Observation fdc35601-a69a-49eb-8b83-ff7e9319b0f3 · outbound

This paper cites Safe Reinforcement Learning in Constrained Markov Decision Processes.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Safe Reinforcement Learning in Constrained Markov Decision Processes

Reference 7

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Observation c6cb463e-ce38-44cc-9444-d781801f1e21 · outbound

This paper cites Safe Reinforcement Learning via Shielding.AAAI, 32(1), April 2018.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Safe Reinforcement Learning via Shielding.AAAI, 32(1), April 2018

Reference 8

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Observation 3582263d-2d16-4753-a0f0-9621a0cbf0a9 · outbound

This paper cites Safe Reinforcement Learning with Nonlinear Dy- namics via Model Predictive Shielding.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Safe Reinforcement Learning with Nonlinear Dy- namics via Model Predictive Shielding

Reference 9

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source=pdf_text observed=2026-08-04T08:23:17.285222Z digest=sha256:8726aec3f737b213591965ceb2f57392ffbbba1297ba5d5f539f64a4d4df931c

Observation 998d193a-75b9-4e03-bd13-e9465e87a9a5 · outbound

This paper cites an unresolved cited work.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-04T08:23:17.380279Z digest=sha256:2dcbc5088760550d2a53d01f47d7f644ac06bd7201e5f31e563a251e8d1c9329

Observation 490d46d0-bf0f-4fc8-b93d-e41402c77adb · outbound

This paper cites Don’t Do Things You Can’t Undo: Reversibility Models for Generating Safe Behaviours.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Don’t Do Things You Can’t Undo: Reversibility Models for Generating Safe Behaviours

Reference 11

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Observation a9f65f6a-489d-4f6c-a1cb-a04375ead61a · outbound

This paper cites Cambridge University Press, 2017.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Cambridge University Press, 2017

Reference 12

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Observation 54401f63-8d5d-4511-a70b-e178a217bf14 · outbound

This paper cites Provable Safe Reinforcement Learning with Binary Feedback.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Provable Safe Reinforcement Learning with Binary Feedback

Reference 13

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Observation 664222e5-c045-424b-a530-f2fe0d5345ba · outbound

This paper cites Long- Term Safe Reinforcement Learning with Binary Feedback.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Long- Term Safe Reinforcement Learning with Binary Feedback

Reference 14

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Observation 264d2a0c-e579-41fc-b2b5-4d689e9e7c31 · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Conservative q-learning for offline reinforcement learning

Reference 15

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Observation 8910cac7-dc28-4891-a1e6-64f93d882b89 · outbound

This paper cites Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning

Reference 16

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Observation ecab50ad-98cc-4e6d-a1f7-812770ed790c · outbound

This paper cites There is no turning back: A self-supervised approach for reversibility-aware reinforcement learning.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control There is no turning back: A self-supervised approach for reversibility-aware reinforcement learning

Reference 17

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source=pdf_text observed=2026-08-04T08:23:18.329391Z digest=sha256:8073dedd7c630d1e55aca2d083a7be550b06dda0925a14b2a8979fd8b766bb28

Observation a2e2688b-4d2a-429b-81a7-68c283a5e5da · outbound

This paper cites Dy- namic model predictive shielding for provably safe reinforcement learning.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Dy- namic model predictive shielding for provably safe reinforcement learning

Reference 18

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Observation ea34a4fd-7ac3-40de-baf5-94c87038145f · outbound

This paper cites Rehg, and Evangelos A.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Rehg, and Evangelos A

Reference 19

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Observation 14589165-7326-40fa-86ab-bda16ccf679e · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 20

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Observation ffdf6320-4555-472b-a790-9f719672b14c · outbound

This paper cites Proximal Policy Optimization Algorithms.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Proximal Policy Optimization Algorithms

Reference 21

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source=pdf_text observed=2026-08-04T08:23:18.680672Z digest=sha256:a8d1a0245a8f27d95ceac2122135304ee9f41396b58a349a44da2ab53493753c

Observation 5651fbe5-046a-4a35-b287-724bf2bbf840 · outbound

This paper cites Stable-baselines3: Reliable reinforcement learning implementations.Journal of Machine Learning Research, 22(268):1–8, 2021.

Approximating Safety Feedback Without a Safety Oracle via Model Predictive Control Stable-baselines3: Reliable reinforcement learning implementations.Journal of Machine Learning Research, 22(268):1–8, 2021

Reference 22

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Pith citing papers

No inbound Pith citation observations are available.