Paper Citation Record · LEDGER

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition

As of 17 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 4 inbound Pith citation observations for arXiv:2505.21571.

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

pith.paper-citation-record.v1
2505.21571 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:50:58.243286Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:44:05.450427Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T12:53:05.833919Z

Reference resolution

68 of 68 outbound references displayed

verified exact0
verified fuzzy36
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c68aff61-e34c-45c5-81d6-8a87d2261427 · outbound

This paper cites Type of modulation identification using wavelet transform and neural network,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Type of modulation identification using wavelet transform and neural network,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.536392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52c4e5da-c68a-4608-a5d9-770801dd832a · outbound

This paper cites Wavelet transform based modula- tion classification for 5g and uav communication in multipath fading channel,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Wavelet transform based modula- tion classification for 5g and uav communication in multipath fading channel,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.587235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77361fac-0a1c-4930-9ca4-b44f954f7f96 · outbound

This paper cites Phasma: An automatic modulation classification system based on random forest,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Phasma: An automatic modulation classification system based on random forest,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.651188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1ab6df0-98b9-449b-af6f-cb9e0aff506b · outbound

This paper cites Cyclic spectral analysis of ofdm/oqam signals,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Cyclic spectral analysis of ofdm/oqam signals,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.730285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c9342f9-e1a1-412c-ba7d-cc818e11e11d · outbound

This paper cites Automatic mod- ulation classification based on high order cumulants and hierarchical polynomial classifiers,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Automatic mod- ulation classification based on high order cumulants and hierarchical polynomial classifiers,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.819634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c652554-48a0-4bf3-846e-93b4f06a3822 · outbound

This paper cites Over-the-air deep learning based radio signal classification,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Over-the-air deep learning based radio signal classification,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.886538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b41b8275-5b4a-47ac-a897-d8ca1c62ce0d · outbound

This paper cites Convolutional radio mod- ulation recognition networks,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Convolutional radio mod- ulation recognition networks,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.936228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04fcb888-f502-4bfe-a9ba-e3ef36dbb170 · outbound

This paper cites An improved neural network pruning technology for automatic modulation classification in edge devices,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition An improved neural network pruning technology for automatic modulation classification in edge devices,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:51.986819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 175f86bf-abff-4149-b029-097d538ad087 · outbound

This paper cites Signet: A novel deep learning framework for radio signal classification,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Signet: A novel deep learning framework for radio signal classification,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:04.474586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 500e8d83-0ed9-4fbf-a007-611864acf92b · outbound

This paper cites Contour stella image and deep learning for signal recognition in the physical layer,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Contour stella image and deep learning for signal recognition in the physical layer,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.113739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9719354-7833-4835-b2f6-e9d5dd6a0683 · outbound

This paper cites Complex-valued networks for automatic modulation classification,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Complex-valued networks for automatic modulation classification,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.177825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cd51e07-9484-452f-a968-79029288157b · outbound

This paper cites Adversarial attacks in modulation recognition with convolutional neural networks,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Adversarial attacks in modulation recognition with convolutional neural networks,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.249428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb9270ea-9093-4489-94a7-78efd82b05a9 · outbound

This paper cites Lightweight automatic modulation classification via progres- sive differentiable architecture search,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Lightweight automatic modulation classification via progres- sive differentiable architecture search,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.308528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42961009-f60b-49a6-b0f1-5900064c59bb · outbound

This paper cites Multi-view discriminant framework for automatic modulation open set recognition,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Multi-view discriminant framework for automatic modulation open set recognition,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.373494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e1c2389-d559-4f15-9788-0aa0c907e6f2 · outbound

This paper cites MCLRL: A Multi-Domain Contrastive Learning with Reinforcement Learning Framework for Few-Shot Modulation Recognition.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition MCLRL: A Multi-Domain Contrastive Learning with Reinforcement Learning Framework for Few-Shot Modulation Recognition

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.419819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4631cb77-fd2a-4ce0-a828-635d0743bedf · outbound

This paper cites Data-driven deep learning for automatic modulation recognition in cognitive radios,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Data-driven deep learning for automatic modulation recognition in cognitive radios,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:04.291195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c4a54990-a6d2-478e-b6e4-fbaa37078a13 · outbound

This paper cites Automatic modulation recognition for spectrum sensing using nonuniform compressive samples,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Automatic modulation recognition for spectrum sensing using nonuniform compressive samples,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:04.109239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 317dc968-d954-4566-b404-2322d8b2fcc2 · outbound

This paper cites A feature weighted hybrid ica-svm approach to automatic modulation recognition,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition A feature weighted hybrid ica-svm approach to automatic modulation recognition,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:03.910156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 485c6085-9734-43a7-9cc1-b9cc128bc4d3 · outbound

This paper cites Automatic modulation recognition of unknown interference signals based on graph model,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Automatic modulation recognition of unknown interference signals based on graph model,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:03.707658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 23c5deff-0e81-4e6e-8a04-406aa5b7d469 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.698347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 013c65c9-26e8-4c4a-b332-27a3e9f20722 · outbound

This paper cites Amc-net: An effective network for automatic modulation classification,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Amc-net: An effective network for automatic modulation classification,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.771352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f060e421-61c3-44f0-9cbd-5d75a8022d58 · outbound

This paper cites Efficient automatic modulation classification in non-terrestrial networks with snn-based transformer,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Efficient automatic modulation classification in non-terrestrial networks with snn-based transformer,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:03.551493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3876cba6-d8e8-4033-ae8e-b66420220456 · outbound

This paper cites Towards building a high-performance intelligent radio network through deep learning: Addressing data privacy, adver- sarial robustness, network structure, and latency requirements.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Towards building a high-performance intelligent radio network through deep learning: Addressing data privacy, adver- sarial robustness, network structure, and latency requirements

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:03.366773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0fe8b002-1c32-4300-9d6f-7af2c57c7003 · outbound

This paper cites Edge learning for b5g networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Edge learning for b5g networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:52.954912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbaabaf2-af25-45a5-9ad9-02998646f9ef · outbound

This paper cites Task- oriented communications for 6g: Vision, principles, and technologies,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Task- oriented communications for 6g: Vision, principles, and technologies,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:53.029958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cff199ea-b03a-4271-ac11-0b29806e8d52 · outbound

This paper cites A systematic dnn weight pruning framework using alternating direction method of multipliers,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition A systematic dnn weight pruning framework using alternating direction method of multipliers,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:03.183224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a254bd20-1362-4822-98e4-06fc96af366e · outbound

This paper cites Pconv: The missing but desirable sparsity in dnn weight pruning for real-time execution on mobile devices,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Pconv: The missing but desirable sparsity in dnn weight pruning for real-time execution on mobile devices,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:02.950381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eef041e7-dc92-4374-8e3a-3408f454daf0 · outbound

This paper cites Combining weight pruning and knowledge distillation for cnn compression,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Combining weight pruning and knowledge distillation for cnn compression,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:02.760688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation af218beb-44c7-4b26-87cb-5512fc89133d · outbound

This paper cites Pruning filter in filter,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Pruning filter in filter,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:02.591348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c6b80503-a383-4f9c-ab8f-ddd07fd6ab67 · outbound

This paper cites Importance estimation for neural network pruning,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Importance estimation for neural network pruning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:02.392715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 455cf491-4d39-417c-ad31-2456c58273d4 · outbound

This paper cites Channel pruning for accelerating very deep neural networks,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Channel pruning for accelerating very deep neural networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:02.230652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c9d1a78c-d8bc-4f8a-8850-a1dcacdc36a3 · outbound

This paper cites Discrimination-aware channel pruning for deep neural networks,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Discrimination-aware channel pruning for deep neural networks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:02.045970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 48c8f65b-d748-4387-9a5b-86b118091be9 · outbound

This paper cites Understanding the dynamics of dnns using graph modularity,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Understanding the dynamics of dnns using graph modularity,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:01.877329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dbef18bb-f16c-4916-8a51-ca37b609f34f · outbound

This paper cites Sr-init: An interpretable layer pruning method,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Sr-init: An interpretable layer pruning method,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:01.739550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3d8a1e3f-53d2-4de5-a962-0a48db4ea70b · outbound

This paper cites Shallowing deep networks: Layer-wise pruning based on feature representations,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Shallowing deep networks: Layer-wise pruning based on feature representations,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:01.563759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d81140c0-3918-4f3f-96d9-9fca8a133c74 · outbound

This paper cites Data-driven sparse structure selection for deep neural networks,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Data-driven sparse structure selection for deep neural networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:01.414482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 73d32736-377f-4e6f-9899-b105dff1953a · outbound

This paper cites A generic layer pruning method for signal modulation recognition deep learning models,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition A generic layer pruning method for signal modulation recognition deep learning models,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:54.324154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a77fbc9f-3a5c-47b5-a901-9a8369f35e12 · outbound

This paper cites Reassessing Layer Pruning in LLMs: New Insights and Methods.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Reassessing Layer Pruning in LLMs: New Insights and Methods

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:54.535902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f5a7474-aa12-4bc9-b5b7-358bbf7b59ca · outbound

This paper cites Rgp: Neural network pruning through regular graph with edges swap- ping,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Rgp: Neural network pruning through regular graph with edges swap- ping,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:54.731261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 018e89b4-335d-4127-ad05-620910b535bb · outbound

This paper cites Radio machine learning dataset generation with gnu radio,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Radio machine learning dataset generation with gnu radio,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:54.865404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1e7457a-a635-45a0-924c-5157c7bbb174 · outbound

This paper cites Filter pruning via measuring feature map information,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Filter pruning via measuring feature map information,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:01.258598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a2c808e7-0619-40c2-ab50-d4aaf89b6478 · outbound

This paper cites Filter pruning via geometric median for deep convolutional neural networks acceleration,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Filter pruning via geometric median for deep convolutional neural networks acceleration,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:01.088450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a3268216-00ff-436a-be2d-1e4631ba6476 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Pruning Filters for Efficient ConvNets

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:55.240309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f32501d-91f8-4542-9392-4cfa764aa0f0 · outbound

This paper cites Soft filter pruning for accelerating deep convolutional neural networks,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Soft filter pruning for accelerating deep convolutional neural networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:00.929437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 75287790-a218-435c-b517-067a61a4b42a · outbound

This paper cites Channel pruning method for signal modulation recognition deep learning models,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Channel pruning method for signal modulation recognition deep learning models,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:00.724880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f0eb0332-431a-4efc-a843-a1915b1a33ee · outbound

This paper cites DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:55.590562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 517e8739-2649-4ea0-bd81-2ea9983c3988 · outbound

This paper cites Lightweight automatic modulation classification based on decentralized learning,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Lightweight automatic modulation classification based on decentralized learning,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:00.538374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cbea6626-3db5-4276-8ce5-30d2ae9ff169 · outbound

This paper cites Nas-amr: Neural architecture search-based automatic mod- ulation recognition for integrated sensing and communication systems,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Nas-amr: Neural architecture search-based automatic mod- ulation recognition for integrated sensing and communication systems,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:00.377586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 18e13ad6-1730-42ab-8c3d-26feaa2f3af8 · outbound

This paper cites Ultra lite convolutional neural network for automatic modulation classification in internet of unmanned aerial vehicles,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Ultra lite convolutional neural network for automatic modulation classification in internet of unmanned aerial vehicles,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:00.203547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 19c93ac3-ff32-491a-b17a-aa3afce05f3d · outbound

This paper cites Pruning neural networks without any data by iteratively conserving synaptic flow,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Pruning neural networks without any data by iteratively conserving synaptic flow,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:56.105469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6daf25-4f50-437f-8787-27b32bbab15c · outbound

This paper cites Deep Model Fusion: A Survey.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Deep Model Fusion: A Survey

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:56.276806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12299d5d-8c5a-4d15-b242-552fbd81aa29 · outbound

This paper cites Merging models with fisher-weighted averaging,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Merging models with fisher-weighted averaging,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:51:00.091492Z

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Observation 61809271-4cd2-4657-be0f-8c96ccf2f541 · outbound

This paper cites Dataless Knowledge Fusion by Merging Weights of Language Models.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Dataless Knowledge Fusion by Merging Weights of Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:56.554806Z

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Observation c36648d1-2e00-4059-b460-a3884b6a0ad7 · outbound

This paper cites PopulAtion Parameter Averaging (PAPA).

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition PopulAtion Parameter Averaging (PAPA)

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:56.696309Z

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Observation 66e090fb-77e9-4c1b-bb0a-a3b87da061ac · outbound

This paper cites Model ratatouille: Recycling diverse models for out-of-distribution gen- eralization,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Model ratatouille: Recycling diverse models for out-of-distribution gen- eralization,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:59.944912Z

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Observation ffc1c792-5b4c-42e9-870c-81572af719d4 · outbound

This paper cites Faster cnns with direct sparse convolutions and guided pruning,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Faster cnns with direct sparse convolutions and guided pruning,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:59.818189Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 478082e7-5d8e-4b45-a7e7-8170a6579ecf · outbound

This paper cites Eie: Efficient inference engine on compressed deep neural network,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Eie: Efficient inference engine on compressed deep neural network,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:59.670042Z

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Observation 6a6903e7-cb7b-4d40-930a-095c7a5a2774 · outbound

This paper cites Robust statistics on riemannian manifolds via the geometric median,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Robust statistics on riemannian manifolds via the geometric median,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:59.518083Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b127322e-7874-4f0d-b313-0b248179428b · outbound

This paper cites To filter prune, or to layer prune, that is the question,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition To filter prune, or to layer prune, that is the question,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:59.349165Z

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Observation fe76a514-356d-4e75-9566-df5d19ad7546 · outbound

This paper cites Hierarchical clustering schemes,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Hierarchical clustering schemes,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:59.188862Z

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Observation 6aa05946-a461-43f7-a992-53930973a26e · outbound

This paper cites Emr- merging: Tuning-free high-performance model merging,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Emr- merging: Tuning-free high-performance model merging,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:57.733402Z

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Observation 2c9c3835-7874-466d-932b-c971570b856c · outbound

This paper cites Ties- merging: Resolving interference when merging models,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Ties- merging: Resolving interference when merging models,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:58.948664Z

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Observation 469d4e00-55d5-4c23-90b4-41aadd2d2ebc · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Averaging Weights Leads to Wider Optima and Better Generalization

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:57.861124Z

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Observation e191e467-5cf5-4df3-b9cf-2bc812617a3a · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:58.805394Z

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Observation 45444254-76e9-49b6-b583-06b517df23c6 · outbound

This paper cites Revisiting Checkpoint Averaging for Neural Machine Translation.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Revisiting Checkpoint Averaging for Neural Machine Translation

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:57.996475Z

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Observation 095fbfbd-e801-49e5-a949-3e5358f0274b · outbound

This paper cites Seasoning model soups for robustness to adversarial and natural distribution shifts,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Seasoning model soups for robustness to adversarial and natural distribution shifts,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:58.666245Z

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Observation 6dffdc4d-65d1-4542-9b43-98ea387e360a · outbound

This paper cites Gnu radio: tools for exploring the radio frequency spec- trum,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Gnu radio: tools for exploring the radio frequency spec- trum,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:58.168289Z

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Observation c0284f58-7af2-4c4e-b21f-9f166017758a · outbound

This paper cites Deep residual learning for image recognition,.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Deep residual learning for image recognition,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:58.537777Z

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Pith citing papers

Observation cdcccab2-eb25-42d3-9cea-3434fc5a8c19 · inbound

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices cites this paper.

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:44:05.450427Z

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Observation b20c43bb-d855-495f-938f-9a25d85662ea · inbound

DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning cites this paper.

DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:02:28.271299Z

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Observation a8ee956e-c199-4e85-95e8-7bc84059e658 · inbound

Multi-Modal Machine Learning Framework for Predicting Early Recurrence of Brain Tumors Using MRI and Clinical Biomarkers cites this paper.

Multi-Modal Machine Learning Framework for Predicting Early Recurrence of Brain Tumors Using MRI and Clinical Biomarkers FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-08-05T12:53:05.838858Z

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Observation c7cad22b-231f-43eb-a238-29bc9f0b38ba · inbound

A Multimodal Deep Learning Framework for Early Diagnosis of Liver Cancer via Optimized BiLSTM-AM-VMD Architecture cites this paper.

A Multimodal Deep Learning Framework for Early Diagnosis of Liver Cancer via Optimized BiLSTM-AM-VMD Architecture FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T12:53:14.905406Z

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