Paper Citation Record · LEDGER

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction

As of 20 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.22640.

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

pith.paper-citation-record.v1
2507.22640 v1

Coverage vector

measured 40 of 40 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-06T11:34:23.413516Z

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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

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation 47d0afb2-e201-4c9c-91b8-555d6cd64d96 · outbound

This paper cites Reinforcement Learning: An Introduction,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Reinforcement Learning: An Introduction,

Reference 1

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Observation 774554ce-b087-4f03-8bc8-5edd85b24f8c · outbound

This paper cites From automated to autonomous process operations,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction From automated to autonomous process operations,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:28.773197Z

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Observation 1c1f6956-1bd8-4db8-b9ec-41dfddbcc373 · outbound

This paper cites Concrete Problems in AI Safety.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Concrete Problems in AI Safety

Reference 3

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Observation 508c8ec1-2f66-422f-a823-a991a2c02b1b · outbound

This paper cites Optimal grade transition for polyethylene reactors via NCO tracking,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Optimal grade transition for polyethylene reactors via NCO tracking,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:28.524681Z

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Observation c5c74b45-b2e3-4584-8979-918730fc3169 · outbound

This paper cites Iterative learning control-based batch process control technique for integrated control of end product properties and transient profiles of process variables,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Iterative learning control-based batch process control technique for integrated control of end product properties and transient profiles of process variables,

Reference 5

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Observation ec392a86-50b6-4a89-922f-37f1aa9bb745 · outbound

This paper cites Integrated scheduling and dynamic optimization of grade transitions for a continuous polymerization reactor,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Integrated scheduling and dynamic optimization of grade transitions for a continuous polymerization reactor,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:28.139301Z

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Observation 99ea38c8-7d60-44dc-b15a-e78182ec8bf7 · outbound

This paper cites The general problem of the stability of motion,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction The general problem of the stability of motion,

Reference 7

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Observation 37dbd767-c63b-4c32-a7f4-cfbedc629599 · outbound

This paper cites an unresolved cited work.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Unresolved cited work

Reference 8

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Observation eb5cd566-8ea5-4177-b7a8-d22666238a99 · outbound

This paper cites Input Convex Neural Networks.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Input Convex Neural Networks

Reference 9

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Observation aeeaa0b7-fca2-4bff-938c-093e73a7bd10 · outbound

This paper cites Safe Model-based Reinforcement Learning with Stability Guarantees.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Safe Model-based Reinforcement Learning with Stability Guarantees

Reference 10

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Observation dc70046b-ce11-4f08-afec-de8e3b61fd2f · outbound

This paper cites Control Barrier Function Based Quadratic Pro- grams for Safety Critical Systems,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Control Barrier Function Based Quadratic Pro- grams for Safety Critical Systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:27.486926Z

Source-reported events for the cited work

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Observation a584b792-8643-44bb-8e73-9c5b521064e9 · outbound

This paper cites Safe and Stable RL (S2RL) Driving Policies Using Control Barrier and Control Lyapunov Functions,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Safe and Stable RL (S2RL) Driving Policies Using Control Barrier and Control Lyapunov Functions,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:27.279331Z

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Observation 6fbb22bf-b6ad-4ad6-a4a7-bd1ad960f3de · outbound

This paper cites Constrained Policy Optimization.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Constrained Policy Optimization

Reference 13

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Source-reported events for the cited work

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Observation 3d6583d2-0b5b-4715-98a1-3576e07c9e16 · outbound

This paper cites Safe Exploration in Continuous Action Spaces.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Safe Exploration in Continuous Action Spaces

Reference 14

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Source-reported events for the cited work

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Observation 10db63f3-0676-4291-8c36-01bea85205dc · outbound

This paper cites Conservative Q-Learning for Offline Reinforcement Learning.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Conservative Q-Learning for Offline Reinforcement Learning

Reference 15

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Observation c007703d-cd76-4faa-97ee-60b7af00f21f · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Offline Reinforcement Learning with Implicit Q-Learning

Reference 16

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Observation cf93d61e-21ef-4c72-b842-e954f85b855f · outbound

This paper cites MOPO: Model-based Offline Policy Optimization.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction MOPO: Model-based Offline Policy Optimization

Reference 17

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Observation 4ccfd0f9-726d-4af3-afb6-4699c5e56739 · outbound

This paper cites Actor–Critic Physics-Informed Neural Lyapunov Con- trol,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Actor–Critic Physics-Informed Neural Lyapunov Con- trol,

Reference 18

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Observation 96778281-0ef6-4a6c-8dc0-c64a2fd2973b · outbound

This paper cites Distributional Reinforcement Learning with Quantile Regression.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Distributional Reinforcement Learning with Quantile Regression

Reference 19

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Observation 370834ac-9400-41f1-a108-4603f8744f26 · outbound

This paper cites EKG-AC: A New Paradigm for Process Indus- trial Optimization Based on Offline Reinforcement Learning With Expert Knowledge Guidance,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction EKG-AC: A New Paradigm for Process Indus- trial Optimization Based on Offline Reinforcement Learning With Expert Knowledge Guidance,

Reference 20

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Observation 3826ad44-7d6d-4395-9796-201a044176c5 · outbound

This paper cites Optimal Control Via Neural Networks: A Convex Approach.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Optimal Control Via Neural Networks: A Convex Approach

Reference 21

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Observation feab1efd-3c40-4dfb-9e6a-13241dd895b7 · outbound

This paper cites Differentiable Convex Optimization Layers.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Differentiable Convex Optimization Layers

Reference 22

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Observation cb8b85ae-3c1d-4330-9859-32c9be6729d1 · outbound

This paper cites OptNet: Differentiable Optimization as a Layer in Neural Networks,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction OptNet: Differentiable Optimization as a Layer in Neural Networks,

Reference 23

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Observation 8d8fd4b8-b759-4fe9-89ab-822f849d849d · outbound

This paper cites Polymer grade transition control using advanced real-time optimization software,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Polymer grade transition control using advanced real-time optimization software,

Reference 24

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Source-reported events for the cited work

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Observation f69c0586-8e19-4c5e-bd61-6aebe21db289 · outbound

This paper cites Polymer grade transition control via reinforcement learning trained with a physically consistent memory sequence-to-sequence digital twin,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Polymer grade transition control via reinforcement learning trained with a physically consistent memory sequence-to-sequence digital twin,

Reference 25

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Observation 0ba9b1af-a386-4ca0-b2af-30e290e13a68 · outbound

This paper cites A benchmark environment motivated by industrial control problems,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction A benchmark environment motivated by industrial control problems,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:25.938005Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e3f99c7-1864-46b0-97c3-b30cd9b1c067 · outbound

This paper cites Benchmarking Batch Deep Reinforcement Learning Algorithms.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Benchmarking Batch Deep Reinforcement Learning Algorithms

Reference 27

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This paper cites PC-Gym: Benchmark Environments For Process Control Problems.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction PC-Gym: Benchmark Environments For Process Control Problems

Reference 28

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Observation eb487b2f-da8a-49e3-86a9-7867a95ee095 · outbound

This paper cites End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

Reference 29

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Observation 203fd197-31c7-47a0-99e1-e90cc81eff2c · outbound

This paper cites Offline reinforcement learning methods for real-world problems,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Offline reinforcement learning methods for real-world problems,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:25.709828Z

Source-reported events for the cited work

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Observation dae50e37-7c3d-4137-9e10-976a79f04421 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 31

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Observation fe6784ac-7e2f-4dcc-b52e-8fa68cd782bf · outbound

This paper cites A survey on offline reinforcement learning: Taxonomy, review, and open problems,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction A survey on offline reinforcement learning: Taxonomy, review, and open problems,

Reference 32

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Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Stabilizing off-policy q-learning via bootstrapping error reduction,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:25.474108Z

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Observation bf7f5e39-0013-46cb-9550-a3bcbe6650ab · outbound

This paper cites Deep Reinforcement Learning with Double Q-learning.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Deep Reinforcement Learning with Double Q-learning

Reference 34

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Observation f22b21aa-dcd3-4daa-a3f5-ab7a82bb7621 · outbound

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Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Human-level control through deep reinforcement learning,

Reference 35

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Observation 2d55ea92-d8cd-437c-b857-b4e5247f3f56 · outbound

This paper cites Behavior Regularized Offline Reinforcement Learning.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Behavior Regularized Offline Reinforcement Learning

Reference 36

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Observation 176e6c8e-b993-44a6-a594-cc0c91212bb0 · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 37

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This paper cites Comparative Study of Machine Learning and System Identification for Process Systems Engineering Dynamics,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Comparative Study of Machine Learning and System Identification for Process Systems Engineering Dynamics,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:25.000267Z

Source-reported events for the cited work

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Observation bc6fd994-6286-4aed-8703-3ba5690351f0 · outbound

This paper cites Polymerization reactor control using autoregressive-plus Volterra- based MPC,.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction Polymerization reactor control using autoregressive-plus Volterra- based MPC,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:34:24.645311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ff2815d-9103-4710-be2f-c89055b741cc · outbound

This paper cites OptNet: Differentiable Optimization as a Layer in Neural Networks.

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction OptNet: Differentiable Optimization as a Layer in Neural Networks

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T11:34:20.749099Z

Source-reported events for the cited work

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Pith citing papers

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