Paper Citation Record · LEDGER

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model

As of 13 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.13763.

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

pith.paper-citation-record.v1
2607.13763 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:50:45.827134Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

32 of 32 outbound references displayed

verified exact0
verified fuzzy0
unresolved32
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 843bca9a-998d-4ce5-bf36-70e9024ff5a9 · outbound

This paper cites Review of load-flow calculation methods,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Review of load-flow calculation methods,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.404943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c492836-d1d2-410e-96f5-cae62e47a158 · outbound

This paper cites A review of graph neural networks and their applications in power systems,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model A review of graph neural networks and their applications in power systems,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.472900Z

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Observation fc041de8-0d50-4bed-a512-1048a8ef3190 · outbound

This paper cites SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.557060Z

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Observation 3caedc99-4250-45f8-99f8-cbecba04c4cb · outbound

This paper cites Graph neural networks: A review of methods and applications,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Graph neural networks: A review of methods and applications,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.647891Z

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Observation 0317cb41-7198-460a-884e-214d8cafeaae · outbound

This paper cites Deepopf+: A deep neural network approach for dc optimal power flow for ensuring feasibility,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Deepopf+: A deep neural network approach for dc optimal power flow for ensuring feasibility,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.713690Z

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Observation c3ac49ec-9c99-4be8-a0b0-ca4dd0629561 · outbound

This paper cites Foundation models for the electric power grid,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Foundation models for the electric power grid,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.801236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 467f6bea-9070-4698-9b4b-8b906e8aa3ca · outbound

This paper cites Recipe for a general, powerful, scalable graph transformer,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Recipe for a general, powerful, scalable graph transformer,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.889001Z

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Unavailable: canonical work link unavailable.

Observation 71c99f4d-6f30-4123-b9b6-d81db0055f65 · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Masked au- toencoders are scalable vision learners,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:43.976154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28acb602-b7db-456e-ac75-9a5480bd0652 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.066127Z

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Unavailable: canonical work link unavailable.

Observation 91fe76b8-64ca-4229-ae03-a688e820eed6 · outbound

This paper cites Attention is all you need,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Attention is all you need,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.133444Z

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Unavailable: canonical work link unavailable.

Observation 9e004e77-03c7-4dc6-a189-d31e8feb5d9c · outbound

This paper cites Moe-graphsage-based integrated evaluation of transient rotor angle and voltage stability in power systems,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Moe-graphsage-based integrated evaluation of transient rotor angle and voltage stability in power systems,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.200274Z

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Unavailable: canonical work link unavailable.

Observation a0c5e4ba-4237-43fc-a3e5-f91f4cc39e2a · outbound

This paper cites Attending to Graph Transformers.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Attending to Graph Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.278014Z

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Observation e2675178-34b0-4dc9-9c7e-8633a54d89db · outbound

This paper cites Residual Gated Graph ConvNets.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Residual Gated Graph ConvNets

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.362087Z

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Observation f145b863-8a6e-49aa-a33d-3a08bf166a7f · outbound

This paper cites Benchmarking graph neural networks,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Benchmarking graph neural networks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.439005Z

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Unavailable: canonical work link unavailable.

Observation 20e1646e-583b-4a7e-a8fd-129d972ebd2a · outbound

This paper cites Graph neural networks with learnable structural and positional representations,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Graph neural networks with learnable structural and positional representations,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.526026Z

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Observation e6484331-334f-4c35-baa8-0f5bbf49fcfc · outbound

This paper cites Heterogeneous graph trans- former,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Heterogeneous graph trans- former,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.579211Z

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Observation 860c9ac6-9ea9-4e45-bee5-fee3a583e609 · outbound

This paper cites Graphmae: Self-supervised masked graph autoencoders,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Graphmae: Self-supervised masked graph autoencoders,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.638118Z

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Observation eb0a1b0c-5f91-4ee2-af49-b11f6998abf2 · outbound

This paper cites Multitask learning,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Multitask learning,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.708044Z

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Observation 9262cffa-9f57-40cf-a656-364749e5efbb · outbound

This paper cites Multi-task graph neural architecture search with task-aware collaboration and curriculum,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Multi-task graph neural architecture search with task-aware collaboration and curriculum,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.766161Z

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Observation f2aa8675-dd6c-4a7a-9977-2c865dc81c74 · outbound

This paper cites Graph mixture of experts: Learning on large-scale graphs with explicit diversity modeling,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Graph mixture of experts: Learning on large-scale graphs with explicit diversity modeling,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.843313Z

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Observation 54e11eda-2a5c-4c88-8891-371988cfc5ce · outbound

This paper cites Mind the links: Cross-layer attention for link prediction in multiplex networks,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Mind the links: Cross-layer attention for link prediction in multiplex networks,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.921752Z

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Observation c20f2261-37d5-4129-bb44-0885ce44cf97 · outbound

This paper cites Physics-informed machine learning,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Physics-informed machine learning,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:44.997575Z

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Observation d1a1d92a-11ea-4dc4-b47d-88afc168d6fe · outbound

This paper cites Language mod- els are few-shot learners,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Language mod- els are few-shot learners,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.056134Z

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Observation 889a29db-1bad-4710-9ec3-9213353954a8 · outbound

This paper cites gridfm-datakit-v1: A python library for scalable and realistic power flow and optimal power flow data generation,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model gridfm-datakit-v1: A python library for scalable and realistic power flow and optimal power flow data generation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.127296Z

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Unavailable: canonical work link unavailable.

Observation 36d90a87-7e8e-44bf-b456-ca4c677f231f · outbound

This paper cites Mat- power: Steady-state operations, planning, and analysis tools for power systems research and education,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Mat- power: Steady-state operations, planning, and analysis tools for power systems research and education,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.217897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95753dd7-2b27-4ba6-87d2-02a4b7cb4021 · outbound

This paper cites The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.290525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d560af0e-fde5-463b-af72-fa020b23eaf3 · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Semi-supervised classification with graph convolutional networks,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.429142Z

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Observation 5c54040f-9e18-48f9-b661-a8f19a9923b9 · outbound

This paper cites Graph attention networks,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Graph attention networks,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.543778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 405f9ebb-3adf-4cd5-8d7d-a43ee8d51735 · outbound

This paper cites How attentive are graph attention net- works?,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model How attentive are graph attention net- works?,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.623526Z

Source-reported events for the cited work

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Observation d1041b02-26b3-4bb9-afd6-16b6931b2edc · outbound

This paper cites Gridsfm: A foundation model for ac optimal power flow.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Gridsfm: A foundation model for ac optimal power flow

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.700855Z

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Observation 9c591dbd-6bb8-4ad6-a771-b4aa267e0bd7 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Fast Graph Representation Learning with PyTorch Geometric

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.771780Z

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Observation 3d94164c-434d-4544-ba4c-a236586ccb80 · outbound

This paper cites Decoupled weight decay regularization,.

MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model Decoupled weight decay regularization,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T03:50:45.827134Z

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Pith citing papers

No inbound Pith citation observations are available.