Paper Citation Record · LEDGER

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks

As of 19 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.19703.

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

pith.paper-citation-record.v1
2506.19703 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:31:08.038667Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

33 of 33 outbound references displayed

verified exact2
verified fuzzy25
unresolved6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a2ca5bb8-ca9c-47c5-b2ce-1259a2a3b183 · outbound

This paper cites Repair and resource scheduling in unbalanced distribution systems using neighborhood search,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Repair and resource scheduling in unbalanced distribution systems using neighborhood search,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.407231Z

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 3f165388-e78f-43aa-89a6-bf336937073a · outbound

This paper cites Power distribution system outage management with co-optimization of repairs, reconfiguration, and dg dispatch,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Power distribution system outage management with co-optimization of repairs, reconfiguration, and dg dispatch,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.396108Z

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 a89bd4cf-be8f-46f9-beec-3dbe7ca7fc40 · outbound

This paper cites Resilient disaster recovery logistics of distribution systems: Co-optimize service restoration with repair crew and mobile power source dispatch,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Resilient disaster recovery logistics of distribution systems: Co-optimize service restoration with repair crew and mobile power source dispatch,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.385487Z

Source-reported events for the cited work

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Observation 4be29f0b-6741-4a67-8b0c-071fdd81c8d8 · outbound

This paper cites The healing touch: Tools and challenges for smart grid restoration,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks The healing touch: Tools and challenges for smart grid restoration,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.375433Z

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

Observation 778bfca0-a3ea-4629-9195-e60c4a7a3939 · outbound

This paper cites Dynamic restoration of active distribution networks by coordinated repair crew dispatch and cold load pickup,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Dynamic restoration of active distribution networks by coordinated repair crew dispatch and cold load pickup,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.365507Z

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 c77a35b9-aca0-4565-b634-429cf0167597 · outbound

This paper cites Multi-robot task allocation in disaster response: Addressing dynamic tasks with deadlines and robots with range and payload constraints,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Multi-robot task allocation in disaster response: Addressing dynamic tasks with deadlines and robots with range and payload constraints,

Reference 6

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Observation 43452869-8c47-491b-bd4a-738c2d0f91d4 · outbound

This paper cites Optimizing service restoration in distribution systems with uncertain repair time and demand,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Optimizing service restoration in distribution systems with uncertain repair time and demand,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.349269Z

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Observation db05ef11-fb05-4bf0-a727-c0e5586403c6 · outbound

This paper cites Distribution Network Restoration: Resource Scheduling Considering Coupled Transportation-Power Networks.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Distribution Network Restoration: Resource Scheduling Considering Coupled Transportation-Power Networks

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:31:08.111714Z

Source-reported events for the cited work

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Observation d8190c3d-7614-4d11-a9c1-002ebbbf9305 · outbound

This paper cites Attention, learn to solve routing problems!.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Attention, learn to solve routing problems!

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.339668Z

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 6ec6dc5a-988f-4048-baa7-71acd30d2610 · outbound

This paper cites Learning the Multiple Traveling Salesmen Problem with Permutation Invariant Pooling Networks.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Learning the Multiple Traveling Salesmen Problem with Permutation Invariant Pooling Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T18:31:07.966988Z

Source-reported events for the cited work

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Observation 69f6a637-341e-4881-bd3a-8934a0c7fca8 · outbound

This paper cites Learning combinatorial optimization algorithms over graphs,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Learning combinatorial optimization algorithms over graphs,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.329984Z

Source-reported events for the cited work

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Observation b15621d1-84b3-4961-acda-ee9de0adad26 · outbound

This paper cites Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks

Reference 12

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Observation e2559488-7ecc-4dc5-9ae7-bf7ec68fb70d · outbound

This paper cites Learning scalable policies over graphs for multi-robot task allocation using capsule attention net- works,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Learning scalable policies over graphs for multi-robot task allocation using capsule attention net- works,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.320805Z

Source-reported events for the cited work

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Observation 7830fd23-4fb5-49a4-a785-f14a2679c199 · outbound

This paper cites Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:31:08.074465Z

Source-reported events for the cited work

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Observation c5947386-ea6f-46e1-bf0b-70b9a367899f · outbound

This paper cites Fast decision support for air tra ffic management at urban air mobility vertiports using graph learning,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Fast decision support for air tra ffic management at urban air mobility vertiports using graph learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.310023Z

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 9418d58e-3c0e-420c-950b-7209fd464466 · outbound

This paper cites Graph learning based decision support for multi-aircraft take-o ff and landing at urban air mobility vertiports,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Graph learning based decision support for multi-aircraft take-o ff and landing at urban air mobility vertiports,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.298738Z

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 fa8624a6-85ac-46ab-bcbc-ed0bfa3e0013 · outbound

This paper cites Learning to allocate time-bound and dynamic tasks to multiple robots using covariant attention neural networks,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Learning to allocate time-bound and dynamic tasks to multiple robots using covariant attention neural networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.287574Z

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 6a337e22-f452-497e-83a5-dca4f14df19c · outbound

This paper cites Real-time outage management in active distribution networks using reinforcement learning over graphs,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Real-time outage management in active distribution networks using reinforcement learning over graphs,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.276772Z

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 fc4b1a4f-15ea-416c-adb9-b84e68c2babf · outbound

This paper cites Bigraph matching weighted with learnt incentive function for multi-robot task allocation,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Bigraph matching weighted with learnt incentive function for multi-robot task allocation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.266232Z

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 fdd8f15e-d6c1-4cd1-aeed-61693076356f · outbound

This paper cites Neuroevolution in deep neural networks: Current trends and future challenges,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Neuroevolution in deep neural networks: Current trends and future challenges,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.256057Z

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 bcc163e0-c2f2-4b9b-808a-8d191039028e · outbound

This paper cites Adaptive neuroevolution with genetic operator control and two-way complexity variation,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Adaptive neuroevolution with genetic operator control and two-way complexity variation,

Reference 21

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

Observation 61bb49dc-b77f-4e31-82dd-98275774139f · outbound

This paper cites Comparative exploration of three approaches to learning heterogeneous robot swarm operations over abstracted complex adversarial environments.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Comparative exploration of three approaches to learning heterogeneous robot swarm operations over abstracted complex adversarial environments

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.233746Z

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 fbf70e7a-6adb-4089-872e-e5d41fbd0228 · outbound

This paper cites Evolutionary algorithm for solving combinatorial optimization—a review,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Evolutionary algorithm for solving combinatorial optimization—a review,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.222688Z

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Observation fceb6839-2de0-4ac6-9d49-9d970a1836c1 · outbound

This paper cites Gymnasium: A standard interface for reinforcement learning environments,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Gymnasium: A standard interface for reinforcement learning environments,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.212031Z

Source-reported events for the cited work

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Observation 9321b73e-2c8b-4c9d-a6af-bacbc28d3522 · outbound

This paper cites Reference guide: The open distribution system simu- lator (OpenDSS),.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Reference guide: The open distribution system simu- lator (OpenDSS),

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.201080Z

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 6b836988-f13f-4509-b4e3-df4ae75f361b · outbound

This paper cites Opendssdirect. py,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Opendssdirect. py,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.190321Z

Source-reported events for the cited work

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Observation bfb7117b-a639-4a00-8e72-f0aa434fc20e · outbound

This paper cites The hungarian method for the assignment problem,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks The hungarian method for the assignment problem,

Reference 27

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Source-reported events for the cited work

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This paper cites An n ˆ5/2 algorithm for maximum matchings in bipartite graphs,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks An n ˆ5/2 algorithm for maximum matchings in bipartite graphs,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.172640Z

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 d4658e4f-7766-421c-9e6b-451728d2177a · outbound

This paper cites Fast graph representation learning with PyTorch Geometric,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Fast graph representation learning with PyTorch Geometric,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T18:31:08.026585Z

Source-reported events for the cited work

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Observation 66c23be3-8dba-4ff7-8ad3-7bda3b7a64c2 · outbound

This paper cites Weisfeiler and leman go neural: Higher- order graph neural networks,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Weisfeiler and leman go neural: Higher- order graph neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.155975Z

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 3359b0e8-8ffb-47ef-b09e-f2a429c4e5c6 · outbound

This paper cites Osmnx: New methods for acquiring, constructing, ana- lyzing, and visualizing complex street networks,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Osmnx: New methods for acquiring, constructing, ana- lyzing, and visualizing complex street networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.144353Z

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 44dcb543-b3e6-4c92-a182-3b8e9acb46f8 · outbound

This paper cites The ieee 8500-node test feeder,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks The ieee 8500-node test feeder,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:31:08.132905Z

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 6d87ed9d-02f6-43fd-93ef-84ce667e549d · outbound

This paper cites Stable-baselines3: Reliable reinforcement learning implementations,.

Learning-aided Bigraph Matching Approach to Multi-Crew Restoration of Damaged Power Networks Coupled with Road Transportation Networks Stable-baselines3: Reliable reinforcement learning implementations,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T18:31:08.038667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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