Paper Citation Record · LEDGER

Revisiting Deep AC-OPF

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2509.00655.

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

pith.paper-citation-record.v1
2509.00655 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:25:26.829995Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

31 of 31 outbound references displayed

verified exact8
verified fuzzy11
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch6

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac325bdf-5c0f-44ba-8e8b-192f1c3d7569 · outbound

This paper cites A rewriting system for convex optimization problems.

Revisiting Deep AC-OPF A rewriting system for convex optimization problems

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.263805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 301c7b30-e3bb-428d-b8b6-e5a47261c3a8 · outbound

This paper cites Under what conditions does e[f(x)] f(e[x]) ? Mathematics Stack Exchange, 2019.

Revisiting Deep AC-OPF Under what conditions does e[f(x)] f(e[x]) ? Mathematics Stack Exchange, 2019

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-05T13:25:28.079529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation feac078b-01c9-4bbd-90e1-80b6ed974c08 · outbound

This paper cites Emulating AC OPF solvers for Obtaining Sub-second Feasible, Near-Optimal Solutions.

Revisiting Deep AC-OPF Emulating AC OPF solvers for Obtaining Sub-second Feasible, Near-Optimal Solutions

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:25:27.996600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fa4040bf-64a1-46a2-b535-6c4462f41514 · outbound

This paper cites CVXPY : A P ython-embedded modeling language for convex optimization.

Revisiting Deep AC-OPF CVXPY : A P ython-embedded modeling language for convex optimization

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.222911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5f05bd07-e9e5-4ccc-b8b4-779dd9587f3d · outbound

This paper cites Neural networks for power flow: Graph neural solver.

Revisiting Deep AC-OPF Neural networks for power flow: Graph neural solver

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.198893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4fc608d3-7e5b-4e41-8eaf-944e1aa22151 · outbound

This paper cites Machine learning for sustainable energy systems.

Revisiting Deep AC-OPF Machine learning for sustainable energy systems

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.184467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 980e11e0-60f3-41ce-810e-9f6f411f0692 · outbound

This paper cites Enforcing robust control guarantees within neural network policies.

Revisiting Deep AC-OPF Enforcing robust control guarantees within neural network policies

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:25:27.978386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d81c80c6-bd42-4604-8021-3fc4ef9b5e5d · outbound

This paper cites Donti, David Rolnick, and J.

Revisiting Deep AC-OPF Donti, David Rolnick, and J

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.171845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8acc4205-d3b4-44e3-936f-5b6ba1be7d1d · outbound

This paper cites Deep learning architectures for inference of AC-OPF solutions.

Revisiting Deep AC-OPF Deep learning architectures for inference of AC-OPF solutions

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:25:27.959643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7b72a1c2-65a8-4906-a603-76aa8c5132bb · outbound

This paper cites Leveraging power grid topology in machine learning assisted optimal power flow.

Revisiting Deep AC-OPF Leveraging power grid topology in machine learning assisted optimal power flow

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.159454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e11faade-9ae2-42bb-bdb2-baeac996ef6f · outbound

This paper cites Power flow balancing with decentralized graph neural networks.

Revisiting Deep AC-OPF Power flow balancing with decentralized graph neural networks

Reference 11

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T13:25:27.940105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 21438032-668f-485f-8176-c88859fbff95 · outbound

This paper cites Deepopf-v: Solving ac-opf problems efficiently.

Revisiting Deep AC-OPF Deepopf-v: Solving ac-opf problems efficiently

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.146509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7f23c781-b138-4c9f-a61c-b2625101f1a9 · outbound

This paper cites OPFLearnData: Dataset for Learning AC Optimal Power Flow.

Revisiting Deep AC-OPF OPFLearnData: Dataset for Learning AC Optimal Power Flow

Reference 13

Resolution: verified exact; doi, observed 2026-08-05T13:25:26.866093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e28daa5c-2ab0-47b1-a4c1-bf5444cbafc6 · outbound

This paper cites an unresolved cited work.

Revisiting Deep AC-OPF Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T13:25:26.763513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d269469-533e-49ff-ab0b-9d80ed211c92 · outbound

This paper cites Numerical comparisons of linear power flow approximations: Optimality, feasibility, and computation time.

Revisiting Deep AC-OPF Numerical comparisons of linear power flow approximations: Optimality, feasibility, and computation time

Reference 15

Resolution: verified exact; raw_fallback, observed 2026-08-05T13:25:27.803014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a032ab1f-bd0b-4e67-a616-2e465babfe40 · outbound

This paper cites an unresolved cited work.

Revisiting Deep AC-OPF Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T13:25:26.770817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4bae55e-e2ff-4b5a-9926-72d63283c0b1 · outbound

This paper cites DeepOPF-U: A Unified Deep Neural Network to Solve AC Optimal Power Flow in Multiple Networks.

Revisiting Deep AC-OPF DeepOPF-U: A Unified Deep Neural Network to Solve AC Optimal Power Flow in Multiple Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T13:25:26.774689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27c0333d-a370-47b4-aac6-7e69d62e0e05 · outbound

This paper cites Topology-aware graph neural networks for learning feasible and adaptive ac-opf solutions.

Revisiting Deep AC-OPF Topology-aware graph neural networks for learning feasible and adaptive ac-opf solutions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.133688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 079b1612-178e-42af-9690-0a60aa9c6002 · outbound

This paper cites Optimal power flow using graph neural networks.

Revisiting Deep AC-OPF Optimal power flow using graph neural networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T13:25:26.782845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32975b81-5dfb-4c51-8714-73676e5b435a · outbound

This paper cites Unsupervised Optimal Power Flow Using Graph Neural Networks.

Revisiting Deep AC-OPF Unsupervised Optimal Power Flow Using Graph Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T13:25:26.786914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccb2e160-acab-440f-b599-28398cd43aec · outbound

This paper cites Reduced optimal power flow using graph neural network.

Revisiting Deep AC-OPF Reduced optimal power flow using graph neural network

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.120795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0b455a42-602a-4b9b-b053-0a2f17beedc8 · outbound

This paper cites CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations.

Revisiting Deep AC-OPF CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T13:25:26.794918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 982f7fcf-cd08-4c81-81b2-b81836b3be04 · outbound

This paper cites Learning an Optimally Reduced Formulation of OPF through Meta-optimization.

Revisiting Deep AC-OPF Learning an Optimally Reduced Formulation of OPF through Meta-optimization

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:25:27.478226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 338e7b0e-5dac-4be4-b67d-8b57c1ed3a84 · outbound

This paper cites Linear power flow calculation methods for urban network.

Revisiting Deep AC-OPF Linear power flow calculation methods for urban network

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-05T13:25:27.459244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2f4de27a-5300-4772-8900-b27b0a024a47 · outbound

This paper cites A state-independent linear power flow model with accurate estimation of voltage magnitude.

Revisiting Deep AC-OPF A state-independent linear power flow model with accurate estimation of voltage magnitude

Reference 25

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T13:25:27.366965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation baaf79d2-9982-4d6c-99a4-678607f8edea · outbound

This paper cites A novel network model for optimal power flow with reactive power and network losses.

Revisiting Deep AC-OPF A novel network model for optimal power flow with reactive power and network losses

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.108116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a344c91c-2a89-4314-93da-e978c9219ae1 · outbound

This paper cites A linearized opf model with reactive power and voltage magnitude: A pathway to improve the mw-only dc opf.

Revisiting Deep AC-OPF A linearized opf model with reactive power and voltage magnitude: A pathway to improve the mw-only dc opf

Reference 27

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T13:25:27.278105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e48c9cd3-5e2c-4423-a0b0-04d4f42984de · outbound

This paper cites A general formulation of linear power flow models: Basic theory and error analysis.

Revisiting Deep AC-OPF A general formulation of linear power flow models: Basic theory and error analysis

Reference 28

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T13:25:27.198587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 33b05fb5-e5c1-405b-a6d8-d11ec6a7be2c · outbound

This paper cites Heydt, Vijay Vittal, and Jaime Quintero.

Revisiting Deep AC-OPF Heydt, Vijay Vittal, and Jaime Quintero

Reference 29

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T13:25:27.090204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f178c72c-eff4-4bb5-8202-85a61da45dc7 · outbound

This paper cites an unresolved cited work.

Revisiting Deep AC-OPF Unresolved cited work

Reference 30

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T13:25:27.014117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fedc7550-e3fc-4eac-b991-b0c3ce95e4ff · outbound

This paper cites Matpower.

Revisiting Deep AC-OPF Matpower

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:25:28.094877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.