Paper Citation Record · LEDGER

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems

As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.19476.

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

pith.paper-citation-record.v1
2506.19476 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:42:12.795046Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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 exact1
verified fuzzy25
unresolved6
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fa5b78d8-6b49-46a6-8902-2e30ea008842 · outbound

This paper cites Application of machine learning in wireless networks: Key techniques and open issues,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Application of machine learning in wireless networks: Key techniques and open issues,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.842526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 095b7fa1-aaea-438d-af80-a660b65ba682 · outbound

This paper cites Intelligent radio signal processing: A survey,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Intelligent radio signal processing: A survey,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.809576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d53243c4-3389-40fe-8c6e-b9dcc66ec123 · outbound

This paper cites Power of deep learning for channel estimation and signal detection in ofdm systems,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Power of deep learning for channel estimation and signal detection in ofdm systems,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.780610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0b10642b-38bd-47ac-bfff-53380ed41fbd · outbound

This paper cites Deep learning for joint channel estimation and signal detection in ofdm systems,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Deep learning for joint channel estimation and signal detection in ofdm systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.755369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b16bceef-088b-4478-90f2-52e5daa3d209 · outbound

This paper cites Deep learning-based end-to- end wireless communication systems with conditional gans as unknown channels,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Deep learning-based end-to- end wireless communication systems with conditional gans as unknown channels,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.727289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cbe178e4-d55b-48a6-a0ff-d12894645c09 · outbound

This paper cites Deep learning based end-to-end wireless communication systems without pilots,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Deep learning based end-to-end wireless communication systems without pilots,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.700297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 42724d38-d2e8-4cc0-b726-6010dd493178 · outbound

This paper cites Deeprx: Fully convolutional deep learning receiver,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Deeprx: Fully convolutional deep learning receiver,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.675655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 69cee451-9cef-44f7-8939-5e93363c809e · outbound

This paper cites Beam Prediction based on Large Language Models.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Beam Prediction based on Large Language Models

Reference 8

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Source-reported events for the cited work

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Observation 111f59fd-ca16-4e88-9ab6-43a2904e2dc9 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Communication-efficient learning of deep networks from decentralized data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.652531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d10b2a59-8d17-467f-a72e-f0f61b8a2220 · outbound

This paper cites Federated learning and wireless commu- nications,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Federated learning and wireless commu- nications,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.625917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f4ef0633-e359-4816-83e8-45efd48040cb · outbound

This paper cites Federated reinforcement learning for resource allocation in v2x networks,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Federated reinforcement learning for resource allocation in v2x networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.598936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bec7b1ee-f033-49cb-b790-fe34f2eade35 · outbound

This paper cites Rescale-invariant federated reinforce- ment learning for resource allocation in v2x networks,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Rescale-invariant federated reinforce- ment learning for resource allocation in v2x networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.569825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f477193a-27be-442d-aa47-b5d9b3f48517 · outbound

This paper cites New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:42:13.013187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cf401799-d064-4b51-ae06-3ee8e53a6e60 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Federated optimization in heterogeneous networks,

Reference 14

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Source-reported events for the cited work

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Observation d8b14bc9-1f88-493c-bf1f-a3faa0c404f5 · outbound

This paper cites FedAlign: Federated Domain Generalization with Cross-Client Feature Alignment.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems FedAlign: Federated Domain Generalization with Cross-Client Feature Alignment

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:42:12.415839Z

Source-reported events for the cited work

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Observation 2790c05e-b25a-4023-adc6-72f8549fa4f6 · outbound

This paper cites Model-contrastive federated learning,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Model-contrastive federated learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.498275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0a5a1ff4-2c86-4bc5-a184-f3a94c02451a · outbound

This paper cites Federated learning with matched averaging,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Federated learning with matched averaging,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.465690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b699ac51-1fd0-4c55-b4a1-8106e099202b · outbound

This paper cites Prevalence of neural collapse during the terminal phase of deep learning training,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Prevalence of neural collapse during the terminal phase of deep learning training,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.418602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation af113766-9206-499b-aaa7-882b6b57ab6f · outbound

This paper cites Neural collapse: A review on modelling principles and generalization,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Neural collapse: A review on modelling principles and generalization,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.393976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 220aabf4-b2ef-49ea-b49e-4e5d99128228 · outbound

This paper cites A geometric analysis of neural collapse with unconstrained features,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems A geometric analysis of neural collapse with unconstrained features,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.363058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e8975473-b48c-4dda-8347-3fd405a9eae5 · outbound

This paper cites Memorization-dilation: Modeling neural collapse under noise,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Memorization-dilation: Modeling neural collapse under noise,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.340800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cbdbc595-62c2-437b-8b5d-b7cc87dd3d75 · outbound

This paper cites Inducing neural collapse in imbalanced learning: Do we really need a learnable classifier at the end of deep neural network?.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Inducing neural collapse in imbalanced learning: Do we really need a learnable classifier at the end of deep neural network?

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.308091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b9930a52-9488-420b-88db-c1255989495d · outbound

This paper cites Neural Collapse in Multi-label Learning with Pick-all-label Loss.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Neural Collapse in Multi-label Learning with Pick-all-label Loss

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T18:42:12.552569Z

Source-reported events for the cited work

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Observation 60cf0faa-3aa4-45e3-944b-fa6aef62db14 · outbound

This paper cites The prevalence of neural collapse in neural multivariate regression,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems The prevalence of neural collapse in neural multivariate regression,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.281045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 459f1603-77b1-47b9-9125-2793ae317217 · outbound

This paper cites Deeply-supervised nets,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Deeply-supervised nets,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.253210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6d0f2da8-cdd5-4d08-813f-bff5f50addde · outbound

This paper cites A Comprehensive Review on Deep Supervision: Theories and Applications.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems A Comprehensive Review on Deep Supervision: Theories and Applications

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:42:12.750230Z

Source-reported events for the cited work

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Observation ab7975f4-aa0b-46b7-baa2-2110e45e0259 · outbound

This paper cites 3d deeply supervised network for automatic liver segmentation from ct volumes,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems 3d deeply supervised network for automatic liver segmentation from ct volumes,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.213920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1f2152bc-2cb4-4d4a-8130-07a5c2f192e9 · outbound

This paper cites Sne-roadseg+: Rethinking depth- normal translation and deep supervision for freespace detection,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Sne-roadseg+: Rethinking depth- normal translation and deep supervision for freespace detection,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.189112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9cfdb87e-3cc7-465e-a525-742b6b63e101 · outbound

This paper cites Deeply-recursive convolutional network for image super-resolution,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Deeply-recursive convolutional network for image super-resolution,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.155338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc09d883-e2a9-498e-bb28-13cb115ecee6 · outbound

This paper cites Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.125831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0b4d8c7b-727e-4290-b99a-7d24b570e400 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Adam: A Method for Stochastic Optimization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T18:42:12.787327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0e63730-2668-4945-8fc2-2e8deb3e10fd · outbound

This paper cites Winner ii channel models,.

Neural Collapse based Deep Supervised Federated Learning for Signal Detection in OFDM Systems Winner ii channel models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:42:13.095669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.