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Paper Citation Record · LEDGER

Modular PE-Structured Learning for Cross-Task Wireless Communications

As of 9 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2509.08614.

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

pith.paper-citation-record.v1
2509.08614 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:27:46.654531Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

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External citation measurements

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Outbound references

Observation f188f366-2759-4633-8b87-ab388b1429ee · outbound

This paper cites A Survey of Large Language Models.

Modular PE-Structured Learning for Cross-Task Wireless Communications A Survey of Large Language Models

Reference 1

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Observation 3503f802-1fc8-4b00-a31f-e3eeb953fb8f · outbound

This paper cites Large Language Model Enabled Multi-Task Physical Layer Network.

Modular PE-Structured Learning for Cross-Task Wireless Communications Large Language Model Enabled Multi-Task Physical Layer Network

Reference 2

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Observation 77c1844c-5673-43a8-b144-f9e4c2dbcfed · outbound

This paper cites LLM4WM: Adapting LLM for Wireless Multi-Tasking.

Modular PE-Structured Learning for Cross-Task Wireless Communications LLM4WM: Adapting LLM for Wireless Multi-Tasking

Reference 3

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Observation 89d1d864-5436-4479-bb74-b55d4496fd01 · outbound

This paper cites WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication.

Modular PE-Structured Learning for Cross-Task Wireless Communications WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication

Reference 4

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Observation 64a89c88-9300-4a47-942f-4de60da8c2c1 · outbound

This paper cites A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges.

Modular PE-Structured Learning for Cross-Task Wireless Communications A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 5

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Observation c17ad815-65d0-45fd-9788-1f6e00ddd62b · outbound

This paper cites From multilayer perceptron to GPT: A reflection on deep learning research for wireless physical layer,.

Modular PE-Structured Learning for Cross-Task Wireless Communications From multilayer perceptron to GPT: A reflection on deep learning research for wireless physical layer,

Reference 6

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Observation d6801785-b7f9-41e5-9aed-e26e5741b8f2 · outbound

This paper cites Understanding the performance of learn- ing precoding policies with graph and convolutional neural networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Understanding the performance of learn- ing precoding policies with graph and convolutional neural networks,

Reference 7

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Observation e82e1234-0908-4ae2-b42d-6319bfaf3b10 · outbound

This paper cites Graph neural networks for scalable ra- dio resource management: Architecture design and theoretical analysis,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Graph neural networks for scalable ra- dio resource management: Architecture design and theoretical analysis,

Reference 8

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Observation b5b82c31-383d-49f5-a55f-5c5fbc996e16 · outbound

This paper cites Learning Precoding in Multi-user Multi-antenna Systems: Transformer or Graph Transformer?.

Modular PE-Structured Learning for Cross-Task Wireless Communications Learning Precoding in Multi-user Multi-antenna Systems: Transformer or Graph Transformer?

Reference 9

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Observation 4e654be1-e479-422a-9e94-c19a133ffb7a · outbound

This paper cites Attention is all you need,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Attention is all you need,

Reference 10

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source=pdf_text observed=2026-08-04T20:27:46.543971Z digest=sha256:51cf34ca7da440d48ebee8b60fc9d6aab6c6b45da7f60c00af06585bb4d1d78e

Observation 7af53f72-c1ab-4100-9177-ea2d42b158a5 · outbound

This paper cites Transformer-empowered 6G intelli- gent networks: From massive MIMO processing to semantic communi- cation,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Transformer-empowered 6G intelli- gent networks: From massive MIMO processing to semantic communi- cation,

Reference 11

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Observation 238b9f3a-e335-4e5c-8b8b-f00d71f82cb6 · outbound

This paper cites Accurate channel prediction based on Transformer: Making mobility negligible,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Accurate channel prediction based on Transformer: Making mobility negligible,

Reference 12

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Observation 5e9896ec-34f5-462e-bafb-36eab2bb3ece · outbound

This paper cites Linformer: A linear-based lightweight Transformer architecture for time-aware MIMO channel prediction,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Linformer: A linear-based lightweight Transformer architecture for time-aware MIMO channel prediction,

Reference 13

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Observation e3831188-dfbf-4ae0-84f5-cd85fc016773 · outbound

This paper cites Pay less but get more: A dual-attention- based channel estimation network for massive MIMO systems with low- density pilots,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Pay less but get more: A dual-attention- based channel estimation network for massive MIMO systems with low- density pilots,

Reference 14

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Observation 6375050c-7745-4aaf-91ec-b2ee8d3a3008 · outbound

This paper cites Transformer-assisted parametric CSI feedback for mmWave massive MIMO systems,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Transformer-assisted parametric CSI feedback for mmWave massive MIMO systems,

Reference 15

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Observation f8118124-f2c4-4b69-9c89-e48795ee64a9 · outbound

This paper cites KANsformer for scalable beamforming,.

Modular PE-Structured Learning for Cross-Task Wireless Communications KANsformer for scalable beamforming,

Reference 16

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Observation 85cfddb6-470a-4f2b-94e5-c371f9c0e123 · outbound

This paper cites Joint spectrum, precoding, and phase shifts design for RIS-Aided multiuser MIMO THz systems,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Joint spectrum, precoding, and phase shifts design for RIS-Aided multiuser MIMO THz systems,

Reference 17

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Observation efb88bca-9bf7-421d-96c8-021567d3c90c · outbound

This paper cites Channel characteristics-based domain adaptation for multiuser MISO beamforming with Transformer and spiking neural networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Channel characteristics-based domain adaptation for multiuser MISO beamforming with Transformer and spiking neural networks,

Reference 18

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Observation 16f0b0e2-dfb0-453c-9b14-08e6b480feb2 · outbound

This paper cites Adaptive TTD configurations for near- field communications: An unsupervised Transformer approach,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Adaptive TTD configurations for near- field communications: An unsupervised Transformer approach,

Reference 19

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Observation 753cacfd-f30b-415c-ad4e-b7327c4e381f · outbound

This paper cites HPE Transformer: Learning to optimize multi-group multicast beamforming under nonconvex QoS constraints,.

Modular PE-Structured Learning for Cross-Task Wireless Communications HPE Transformer: Learning to optimize multi-group multicast beamforming under nonconvex QoS constraints,

Reference 20

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Observation 50600199-231c-41df-b5c3-aae8dc972882 · outbound

This paper cites Multidimensional graph neural networks for wireless communications,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Multidimensional graph neural networks for wireless communications,

Reference 21

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source=pdf_text observed=2026-08-04T20:27:46.577413Z digest=sha256:dfa6fac3fbbedd6b0f7ffed5fb1a9d787d7374e0f2ae65067295bc7f0fb0cb4f

Observation 42f197be-73a0-425e-9015-a808286baa1e · outbound

This paper cites RE-MIMO: Recurrent and permutation equivariant neural MIMO detection,.

Modular PE-Structured Learning for Cross-Task Wireless Communications RE-MIMO: Recurrent and permutation equivariant neural MIMO detection,

Reference 22

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Observation 3659131c-a6d0-474e-ba09-c3997feda37c · outbound

This paper cites Learning power allocation for multi-cell-multi- user systems with heterogeneous graph neural networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Learning power allocation for multi-cell-multi- user systems with heterogeneous graph neural networks,

Reference 23

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source=pdf_text observed=2026-08-04T20:27:46.583326Z digest=sha256:b7e80b9e1c948d2576043012561fd0601cb2e5c2860003b367f1da9626c37d98

Observation d1626438-6724-4682-812d-340a75466199 · outbound

This paper cites Computation offloading and quan- tization schemes for federated satellite-ground graph networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Computation offloading and quan- tization schemes for federated satellite-ground graph networks,

Reference 24

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Observation 914d699a-5117-4893-adde-162c2a28188d · outbound

This paper cites ENGNN: A general edge-update empowered GNN architecture for radio resource management in wireless networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications ENGNN: A general edge-update empowered GNN architecture for radio resource management in wireless networks,

Reference 25

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Observation 936cc477-9c94-4463-8aee-fefa36e444b4 · outbound

This paper cites Improving learning efficiency for wire- less resource allocation with symmetric prior,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Improving learning efficiency for wire- less resource allocation with symmetric prior,

Reference 26

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Observation 2f6c5184-5083-4adb-9cc3-1b58558bf3e9 · outbound

This paper cites Scalable hybrid beamforming for multi- user MISO systems: A graph neural network approach,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Scalable hybrid beamforming for multi- user MISO systems: A graph neural network approach,

Reference 27

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Observation 2738cddd-1127-4061-b09b-1b9696d78d19 · outbound

This paper cites GNN-based beamforming for sum-rate maximization in MU-MISO networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications GNN-based beamforming for sum-rate maximization in MU-MISO networks,

Reference 28

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Observation 965ef1f7-cc77-4c39-aa31-683273edce65 · outbound

This paper cites Recursive GNNs for learning precoding policies with size-generalizability,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Recursive GNNs for learning precoding policies with size-generalizability,

Reference 29

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Observation fa1fd25f-62fb-4a31-9ba1-7f5f08235b6a · outbound

This paper cites Set Transformer: A framework for attention-based permutation-invariant neural networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Set Transformer: A framework for attention-based permutation-invariant neural networks,

Reference 30

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Observation e75bd217-30e0-49b4-80f7-61d190c37cc8 · outbound

This paper cites Transfer learning with reconstruction loss,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Transfer learning with reconstruction loss,

Reference 31

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source=pdf_text observed=2026-08-04T20:27:46.609978Z digest=sha256:bf01a1510fef90bbf96f08578ac90c92c4bca505c0fc3714d63a94947beebc31

Observation 59cf9d5c-fd9e-41be-8627-fb5843953b2d · outbound

This paper cites Deep plug-and-play prior for multitask channel reconstruction in massive MIMO systems,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Deep plug-and-play prior for multitask channel reconstruction in massive MIMO systems,

Reference 32

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Observation 673f0fd3-62a7-450d-8311-3bb85dff029e · outbound

This paper cites A survey on multi-task learning,.

Modular PE-Structured Learning for Cross-Task Wireless Communications A survey on multi-task learning,

Reference 33

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Observation cd804f30-bfd6-4041-9a8e-571eb9e48ea2 · outbound

This paper cites Deep sets,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Deep sets,

Reference 34

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Observation 4b8d63d6-2d40-4fe7-881d-6c0d804bf7cf · outbound

This paper cites An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,.

Modular PE-Structured Learning for Cross-Task Wireless Communications An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,

Reference 35

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Observation 5c9dd956-4b90-4535-b00c-04515c03d908 · outbound

This paper cites Optimal multiuser trans- mit beamforming: A difficult problem with a simple solution structure,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Optimal multiuser trans- mit beamforming: A difficult problem with a simple solution structure,

Reference 36

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Observation 527c6705-4f68-4648-b986-1beb0a464846 · outbound

This paper cites Approximation by superpositions of a sigmoidal function,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Approximation by superpositions of a sigmoidal function,

Reference 37

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Observation f038c83a-3c25-44d4-82ed-10f3de62f333 · outbound

This paper cites Edge-wise gated graph neural network for user association in massive URLLC,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Edge-wise gated graph neural network for user association in massive URLLC,

Reference 38

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Observation d4facd54-cd7e-4344-97b7-23908505ea1a · outbound

This paper cites A deep learning-based framework for low complexity multiuser MIMO precoding design,.

Modular PE-Structured Learning for Cross-Task Wireless Communications A deep learning-based framework for low complexity multiuser MIMO precoding design,

Reference 39

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Observation a258e671-c653-4c1f-aedd-166196f857c9 · outbound

This paper cites Precoding and power optimization in cell-free massive MIMO systems,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Precoding and power optimization in cell-free massive MIMO systems,

Reference 40

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Observation 25f15447-80ee-4596-8c2b-c2bec23397aa · outbound

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

Modular PE-Structured Learning for Cross-Task Wireless Communications Graph embedding-based wireless link scheduling with few training samples,

Reference 41

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Observation 8fa69196-d70b-4024-8185-f539f6b7aa76 · outbound

This paper cites High-generalization real-time beamforming design for dynamic wireless environments in cell-free systems,.

Modular PE-Structured Learning for Cross-Task Wireless Communications High-generalization real-time beamforming design for dynamic wireless environments in cell-free systems,

Reference 42

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Observation 8f2032e2-115b-48fe-8553-bbcc833d7aaf · outbound

This paper cites Coordinated beamforming for MISO interference channel: Complexity analysis and efficient algo- rithms,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Coordinated beamforming for MISO interference channel: Complexity analysis and efficient algo- rithms,

Reference 43

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Observation c18b89a2-b371-41a4-9e26-8a00d1b539c8 · outbound

This paper cites Learning beamforming for RIS-aided systems with permutation equivariant graph neural networks,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Learning beamforming for RIS-aided systems with permutation equivariant graph neural networks,

Reference 44

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Observation eb722aa0-55c7-4715-985c-d071e950ca09 · outbound

This paper cites Learning to beamform for integrated sensing and communication: A graph neural network with implicit projection approach,.

Modular PE-Structured Learning for Cross-Task Wireless Communications Learning to beamform for integrated sensing and communication: A graph neural network with implicit projection approach,

Reference 45

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Pith citing papers

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