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Paper Citation Record · LEDGER

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction

As of 15 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

Typed states for the displayed outbound observations.

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

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

40 of 40 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved20
  • parse uncertain0
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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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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

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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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:17.887751Z digest=sha256:c4ff61953b249efaf63480bc494c3779b9893411c077d3bbbc4b6ab6cfcdc808

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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source=pdf_text observed=2026-08-06T11:34:18.102389Z digest=sha256:d2e4adb2f6808f67b929af99ef2db1f570e4dbd49f7526e35a3075498a307bad

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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source=pdf_text observed=2026-08-06T11:34:18.321318Z digest=sha256:153f57c9f5dceaaa50cadd811456344e7f14b9132e243d0b27306d30f889d658

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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source=pdf_text observed=2026-08-06T11:34:18.448416Z digest=sha256:496c04af527470ad47fcbf5d9ec2c6be27e3751bd4a4a46398feff7407932019

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

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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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:18.749875Z digest=sha256:a75396c04ac8b30f472e98f44f6180f52215fff0c52cbf0ee7239f601bf8ed05

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=pdf_text observed=2026-08-06T11:34:18.893392Z digest=sha256:7e6b5fc87d4b0ccdf3c3bcb31f09cbd4109d2002cdd9d8f980e9afeae8bc773d

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=pdf_text observed=2026-08-06T11:34:19.104125Z digest=sha256:a7e90361945f7cdf1afb4c147eb7ffc63844a3b7897837bb969c985197db3522

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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source=pdf_text observed=2026-08-06T11:34:19.197355Z digest=sha256:f526246a43588344b90f9ffb8136c002ebc4ea0380f3801f25befb3e89584f8f

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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source=pdf_text observed=2026-08-06T11:34:19.560544Z digest=sha256:dfc45353057c01eb1ddb1818b53a6019663fcf9cfb49bd5a1de7da50dcb9f0da

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:19.741550Z digest=sha256:39973f1b085079e93c571f31761de2c802b9bcefbb790bb26efaa523a253ec27

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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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source=pdf_text observed=2026-08-06T11:34:20.306372Z digest=sha256:f9138bc786c4bfdede11b0d3a9a00d56303fa55dd7c2c9823e18872f0a6a7c9a

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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source=pdf_text observed=2026-08-06T11:34:20.442610Z digest=sha256:baa5249bdb747710361da5bf945da12ff184e8f4c2e1fcd5d32e4af281b9fe00

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:21.296216Z digest=sha256:ca60c1fa271bb88a977e708d913bd2c90bb143a0359465664c634b2861443d1b

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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source=pdf_text observed=2026-08-06T11:34:21.442854Z digest=sha256:53fdd6e367efbff49153e3212fbe0b25e2b257941e7616470425c3d1cff58f6a

Observation ef465ad6-a07f-4c36-8315-f2958d7f4a43 · outbound

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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source=pdf_text observed=2026-08-06T11:34:21.584194Z digest=sha256:b9d32a88301f2fa4a282f401e50e7d9fe66ff47760512236c94a5db724444bab

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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local_arxiv, observed 2026-08-06T11:34:23.746247Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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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

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:22.030643Z digest=sha256:7f0992c6e9c09556e0f61e057e8fb45fd8259733ad50d02549c1cdbb9891ba0a

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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source=pdf_text observed=2026-08-06T11:34:22.256553Z digest=sha256:eb7a0862827ac33dbfab7299e637ed256cb64c4f5c783e2f8481102f0988c5af

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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source=pdf_text observed=2026-08-06T11:34:22.483538Z digest=sha256:ec39be053376558b2a89d7650b29e2e169c73bd715dbb8eadd5a18fa8203e2c8

Observation dce9edd8-9547-4c5a-8e76-9faad7a9eafd · outbound

This paper cites Stabilizing off-policy q-learning via bootstrapping error reduction,.

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

Reference 33

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:22.678861Z digest=sha256:588292b3a4734d5b9ffc2ed366e2109e6c2da8bb02f616d8b9499f606789d8f8

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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source=pdf_text observed=2026-08-06T11:34:22.841058Z digest=sha256:4ba3da6d31df416626ebcc4516c79da85634276d71d51c67ffc8ce6fbdb7d4b3

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

This paper cites Human-level control through deep reinforcement learning,.

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

Reference 35

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T11:34:23.006757Z digest=sha256:144f8f1ba1d38393c6704665ab3168c1c481d1ae367f54f7b1750a5b81d6cd5c

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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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Observation 09431ac7-47f5-49c0-a3bc-9ec13e86c089 · outbound

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

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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

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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

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