Paper Citation Record · LEDGER

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.18748.

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

pith.paper-citation-record.v1
2506.18748 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:49:28.809890Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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 fuzzy27
unresolved4
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 37111584-822b-4deb-8ac7-2a16169239bb · outbound

This paper cites ITLinQ: A new approach for spectrum sharing in device-to-device communication systems,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression ITLinQ: A new approach for spectrum sharing in device-to-device communication systems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.474094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 91c091d3-1ab7-4c83-81b7-8bbac6f18cd2 · outbound

This paper cites ITLinQ+: An improved spectrum sharing mechanism for device-to-device communications,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression ITLinQ+: An improved spectrum sharing mechanism for device-to-device communications,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.460405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c26fdc55-2d00-420f-96c4-475cfe220dbd · outbound

This paper cites FPLinQ: A cooperative spectrum sharing strategy for d2d communications,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression FPLinQ: A cooperative spectrum sharing strategy for d2d communications,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.445910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8f69354-6002-4547-add3-a8f4555a6621 · outbound

This paper cites Optimal wireless resource alloca- tion with random edge graph neural networks,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Optimal wireless resource alloca- tion with random edge graph neural networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.432163Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2201aa8b-d243-4f58-abdb-a73d9ac838b1 · outbound

This paper cites Resource management in wireless networks via multi- agent deep reinforcement learning,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Resource management in wireless networks via multi- agent deep reinforcement learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.418312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d79d135-a57d-44f5-9f78-2a58a4393b51 · outbound

This paper cites Intelligent O-RAN for Beyond 5G and 6G Wireless Networks.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Intelligent O-RAN for Beyond 5G and 6G Wireless Networks

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:49:29.070961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 27cec773-17dc-487b-a0cb-e1867ba9099a · outbound

This paper cites Unfolding wmmse using graph neural networks for efficient power allocation,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Unfolding wmmse using graph neural networks for efficient power allocation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.403825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f327699-66f6-4d34-b226-637c5ef2d743 · outbound

This paper cites Unsupervised learning for asynchronous resource allocation in ad-hoc wireless net- works,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Unsupervised learning for asynchronous resource allocation in ad-hoc wireless net- works,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.389764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00f19499-3025-4f1d-8a06-75769cdf03fd · outbound

This paper cites Edge artificial intelligence for 6g: Vision, enabling technologies, and appli- cations,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Edge artificial intelligence for 6g: Vision, enabling technologies, and appli- cations,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.375928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ea9f9ca6-be8b-4945-b749-c38c2cf65e0c · outbound

This paper cites Link scheduling using graph neural networks,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Link scheduling using graph neural networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.361625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b78d4831-a8cf-4930-aebc-23fd8fe323d8 · outbound

This paper cites Modular Meta-Learning for Power Control via Random Edge Graph Neural Networks.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Modular Meta-Learning for Power Control via Random Edge Graph Neural Networks

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f6ccf087-ba8b-46ef-a9f8-00153bbbb1cf · outbound

This paper cites Power allocation for wireless federated learning using graph neural networks,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Power allocation for wireless federated learning using graph neural networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.347932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3e0f035f-c941-4ff7-851c-4e6d2014b6a4 · outbound

This paper cites Regularization strategy aided robust unsupervised learning for wireless resource allocation,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Regularization strategy aided robust unsupervised learning for wireless resource allocation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.333345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c2c42820-8f80-4550-b295-fd84332d979f · outbound

This paper cites Learning to slice wi-fi networks: A state-augmented primal-dual approach,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Learning to slice wi-fi networks: A state-augmented primal-dual approach,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.317900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 34a8a738-0443-4c5c-9665-057218ec47fe · outbound

This paper cites Opportunistic routing in wireless communications via learn- able state-augmented policies,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Opportunistic routing in wireless communications via learn- able state-augmented policies,

Reference 15

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Source-reported events for the cited work

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Observation 99f8f5ab-e736-4182-9fd3-924ba5fae800 · outbound

This paper cites Diffusion model based resource allocation strategy in ultra-reliable wireless networked control systems,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Diffusion model based resource allocation strategy in ultra-reliable wireless networked control systems,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.301676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 96c49452-5502-4b78-ad68-76ddca67414c · outbound

This paper cites Learning optimal resource allocations in wireless systems,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Learning optimal resource allocations in wireless systems,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.286707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1f1b685b-9caa-4ebd-93a3-b253efc3d9a7 · outbound

This paper cites Optimal resource allocation in wireless communi- cation and networking,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Optimal resource allocation in wireless communi- cation and networking,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.272397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ecb8be8-3545-4aa2-bcbe-9d179b4a6ce6 · outbound

This paper cites Learning resilient radio resource management policies with graph neural net- works,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Learning resilient radio resource management policies with graph neural net- works,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.257450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e48dd8d-a88f-473c-b4af-1036defc733b · outbound

This paper cites State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards

Reference 20

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Source-reported events for the cited work

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Observation 5fe09b80-f96b-4acb-963e-21029d308e79 · outbound

This paper cites State- augmented learnable algorithms for resource management in wireless networks,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression State- augmented learnable algorithms for resource management in wireless networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.243681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e6de9853-da54-460e-99b1-071bf6799f2b · outbound

This paper cites Boyd and Lieven Vandenberghe, Convex optimization , Cambridge University Press, 2004.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Boyd and Lieven Vandenberghe, Convex optimization , Cambridge University Press, 2004

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T18:49:28.763838Z

Source-reported events for the cited work

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Observation cc1d7920-c939-4cab-85d5-591859512f2b · outbound

This paper cites 5, Springer Science & Business Media, 2012.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression 5, Springer Science & Business Media, 2012

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.219964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cb94ebbc-b4d9-4e50-bdc7-d7eff365dcce · outbound

This paper cites Near-optimal solutions of constrained learning problems,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Near-optimal solutions of constrained learning problems,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.204425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c70abe03-9e47-450c-953c-e0e9e0fc4bb9 · outbound

This paper cites Ergodic stochastic optimization algorithms for wireless communication and networking,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Ergodic stochastic optimization algorithms for wireless communication and networking,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.190007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0bc7b7ac-c764-4df5-a74c-d7c897f13635 · outbound

This paper cites Inexact stochastic mirror descent for two-stage nonlinear stochastic programs,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Inexact stochastic mirror descent for two-stage nonlinear stochastic programs,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.175379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 332960e9-4a86-4c9e-8ea0-d5652c2e69c1 · outbound

This paper cites Graph embedding- based wireless link scheduling with few training samples,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Graph embedding- based wireless link scheduling with few training samples,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.160215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f658741e-9c4c-4cd7-99c8-997f8dabe229 · outbound

This paper cites A Graph Neural Network Approach for Scalable Wireless Power Control.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression A Graph Neural Network Approach for Scalable Wireless Power Control

Reference 28

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Source-reported events for the cited work

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Observation 6c4424a7-b872-4359-aaa3-9452cae7b0d2 · outbound

This paper cites Ultra-dense networks in 5G: Interference management via non- orthogonal multiple access and treating interference as noise,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Ultra-dense networks in 5G: Interference management via non- orthogonal multiple access and treating interference as noise,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.145362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6dcd79db-289f-4a2a-a13e-068877589aa0 · outbound

This paper cites A convergence theorem for non negative almost supermartingales and some applications,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression A convergence theorem for non negative almost supermartingales and some applications,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.130240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c50bb73d-0a32-4d1b-81dd-e87ee322e8e7 · outbound

This paper cites Shor, n. z., minimization methods for non-differentiable functions.,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Shor, n. z., minimization methods for non-differentiable functions.,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.115451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ed04481-959f-43b0-a13b-d6dc257266a9 · outbound

This paper cites Distributed network optimization with heuristic rational agents,.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Distributed network optimization with heuristic rational agents,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.100813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d64b8263-751f-408a-ab94-57b065af7cd1 · outbound

This paper cites Doob, Stochastic Processes, John Wiley & Sons, New York, 1953.

Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression Doob, Stochastic Processes, John Wiley & Sons, New York, 1953

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:49:29.086207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.