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Paper Citation Record · LEDGER

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis

As of 21 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 0 inbound Pith citation observations for arXiv:2509.08188.

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

pith.paper-citation-record.v1
2509.08188 v1

Coverage vector

measured 82 of 82 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:08:52.234225Z

measured 82 of 82 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

82 of 82 outbound references displayed

  • verified exact7
  • verified fuzzy42
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 946fe481-741f-4809-91af-d4cc96aa9580 · outbound

This paper cites Data augmentation of eeg using gans for emotion recognition.IEEE Transactions on Affective Computing, 2021.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Data augmentation of eeg using gans for emotion recognition.IEEE Transactions on Affective Computing, 2021

Reference 1

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Source-reported events for the cited work

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Observation 5147cb7d-5351-4b33-a9aa-cefd096145c0 · outbound

This paper cites Engemann, and Alexandre Gramfort.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Engemann, and Alexandre Gramfort

Reference 2

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no resolver link, observed 2026-08-04T21:08:41.957999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2abca350-c93c-4d1c-938d-505233d8e42e · outbound

This paper cites classification of covariance matrices using riemannian geometry and its application to brain-computer interfaces.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis classification of covariance matrices using riemannian geometry and its application to brain-computer interfaces

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation a3ea9ecd-e976-43e5-a91e-ace11dd8d28a · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 340b8790-e7a2-40e8-99ca-3dd23db1d1b9 · outbound

This paper cites Demystifying MMD GANs.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Demystifying MMD GANs

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation a49542a1-235a-4eb5-8c41-19905c758d47 · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation ecc296a4-3bf1-4d60-8a21-05d9f5288531 · outbound

This paper cites The secret sharer: Evaluating and testing unintended memorization in neural networks.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis The secret sharer: Evaluating and testing unintended memorization in neural networks

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:06.090936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:42.533866Z digest=sha256:515a1bb6df86842b0329c68ff50aa257b8c8ab8879833eb41cb32b925ed1652c

Observation 8f0c406e-ef88-4562-9014-6c40c414c87d · outbound

This paper cites Extracting training data from diffusion models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Extracting training data from diffusion models

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation dd3a7886-4ef4-4d92-8a94-10fd79cbd78d · outbound

This paper cites Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:08:54.407971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 5fa37376-ff52-4974-84d9-1ce6127c5e2f · outbound

This paper cites WaveGrad: Estimating Gradients for Waveform Generation.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis WaveGrad: Estimating Gradients for Waveform Generation

Reference 10

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unresolved
no resolver link, observed 2026-08-04T21:08:42.935239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f3af7a2e-4007-4cf3-827a-e1562d482df1 · outbound

This paper cites Eeg artifact simulation for training robust deep networks.Frontiers in Neuroinformatics, 16:835699, 2022.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Eeg artifact simulation for training robust deep networks.Frontiers in Neuroinformatics, 16:835699, 2022

Reference 11

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verified fuzzy
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Source-reported events for the cited work

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Observation 5bb2ea68-9b63-41de-9d88-bbd8666d6f99 · outbound

This paper cites Image-based Data Representations of Time Series: A Comparative Analysis in EEG Artifact Detection.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Image-based Data Representations of Time Series: A Comparative Analysis in EEG Artifact Detection

Reference 12

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation d8dba2d8-d0e5-4da9-9001-c68a106a03bd · outbound

This paper cites Diffusion models beat gans on image synthesis.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Diffusion models beat gans on image synthesis

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 69bb53cc-6d0e-4932-a627-64c653849f96 · outbound

This paper cites Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective

Reference 14

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verified exact
local_arxiv, observed 2026-08-04T21:08:53.758037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:43.448833Z digest=sha256:18aa246ea8064dee1de2c60935e9ac55c75da7c6ff7b5f0cd628c52a00bbe419

Observation 832bfeed-ad65-4617-bb9a-9a270fdd3344 · outbound

This paper cites Adversarial audio synthesis.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Adversarial audio synthesis

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 0b81d809-4881-4b75-847d-126b36df4a9b · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation e37582a3-582b-4359-b4c6-da51de9bbad9 · outbound

This paper cites Hyland, and Gunnar Rätsch.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Hyland, and Gunnar Rätsch

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 0edb98ea-65f5-4b3a-b231-de57d849390d · outbound

This paper cites Goldberger, Luis A.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Goldberger, Luis A

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 919a1a3d-08ee-40eb-a5ac-889c154f410e · outbound

This paper cites a kernel two-sample test.Journal of Machine Learning Research, 13(25):723–773, 2012.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis a kernel two-sample test.Journal of Machine Learning Research, 13(25):723–773, 2012

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9f43d134-fb28-4d87-a303-324b7965aff7 · outbound

This paper cites Improved training of wasserstein gans.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Improved training of wasserstein gans

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 0807b4b7-d27b-4fe4-ad57-1dcd0b05a6ab · outbound

This paper cites Habashi, Ahmed M.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Habashi, Ahmed M

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7f743dd0-99c1-48c2-bde0-b4d8a08e1244 · outbound

This paper cites Hamid, K.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Hamid, K

Reference 22

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raw_fallback, observed 2026-08-04T21:09:03.734166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation fe4fce7b-8f89-440a-af29-0faa518c6285 · outbound

This paper cites EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:44.644481Z digest=sha256:b304700a40255c60b1cf411cd91cbb4ba22b765ad5cdd3e4b29166deafa6ee87

Observation 88620d00-e3d8-4360-91a4-31e0204bc9bb · outbound

This paper cites deep residual learning for image recognition.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis deep residual learning for image recognition

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:44.796100Z digest=sha256:1442b03f4e4340ff3e67f0ce193bdb96a5fbcfbe1ecf091494f4488684919fa4

Observation c6006937-b029-436f-ad9e-e9f9baca6a17 · outbound

This paper cites Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshmi- narayanan.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshmi- narayanan

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 4454f6fc-6417-43cd-bb42-51d9f8a40390 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3ba33b10-c216-421b-b47e-50bb8a81bf27 · outbound

This paper cites Denoising diffusion probabilistic models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Denoising diffusion probabilistic models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:45.169175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:45.169175Z digest=sha256:7b5f81759fdb0d873b93cd72cd42bfee1f4c341cc1389fecf30246d74cfd3ba4

Observation 7109e114-168e-4645-b239-64e3cf180e2e · outbound

This paper cites Classifier-Free Diffusion Guidance.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Classifier-Free Diffusion Guidance

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:45.283974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:45.283974Z digest=sha256:60aee65b2255da056e3a9c4d15dcf5819fc3c9258b8ad6f4121b9e4fbb2c7b8b

Observation fae5c88e-daf0-49ae-9499-e2faa6170cea · outbound

This paper cites Energy-Efficient Tree-Based EEG Artifact Detection.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Energy-Efficient Tree-Based EEG Artifact Detection

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:08:53.421455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9d78adb3-4347-4674-97ab-a746b41b6101 · outbound

This paper cites Jackson and Luis M.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Jackson and Luis M

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:02.938594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:45.519999Z digest=sha256:91367bb6073e6912b2c2eb0217a989e83a4b0795371d235110ca7235e3ac6a1f

Observation 252e135f-bc97-44fb-836a-c47e0f2713b8 · outbound

This paper cites Removal of artifacts from eeg signals: A review.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Removal of artifacts from eeg signals: A review

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:02.718673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:45.609344Z digest=sha256:11e7c0ab4e86b57d31accac073bc744b67e269030411f102e014baa87eb138c2

Observation cb24db13-c13b-443b-9ef7-273fff8f78c5 · outbound

This paper cites Aneeg: Leveraging deep learning for effective artifact removal in eeg data.Scientific Reports, 14(1):14761, 2024.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Aneeg: Leveraging deep learning for effective artifact removal in eeg data.Scientific Reports, 14(1):14761, 2024

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:02.389501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:45.707277Z digest=sha256:ad1270a1dd95c19aeb606177ec7524c99b532e6c3b6c881782233c78194783be

Observation 5893a1ad-db96-4a2a-9d2a-7d02a0be1013 · outbound

This paper cites elucidating the design space of diffusion-based generative models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis elucidating the design space of diffusion-based generative models

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-04T21:09:02.124378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:45.834878Z digest=sha256:62bf8d0fda7d04f8cac4e3be91a9d218cfc75a50b40efeb09f1ac3c5cb9ea97a

Observation 1958ea62-2893-4005-b0cf-32d6a15ff6de · outbound

This paper cites The tuh abnormal expansion eeg corpus (tuabex).NeuroImage: Clinical, 38:103317, 2023.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis The tuh abnormal expansion eeg corpus (tuabex).NeuroImage: Clinical, 38:103317, 2023

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:01.910931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:45.950181Z digest=sha256:ad10b076d27c0329fa3f2fe40a395c86a9ddf6580f7efef2f631abb1ec55b16b

Observation db42b7da-1cd1-4fbc-89b5-338258232d2e · outbound

This paper cites Fr\'echet Audio Distance: A Metric for Evaluating Music Enhancement Algorithms.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Fr\'echet Audio Distance: A Metric for Evaluating Music Enhancement Algorithms

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:46.035792Z digest=sha256:da467b34d5e7d4039193597a6173d2e70bafb115feaa7263a4242d1dd984a168

Observation 1db35f57-09ea-4bd0-82b9-b1dde50af6c4 · outbound

This paper cites Adam: A method for stochastic optimization.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Adam: A method for stochastic optimization

Reference 36

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no resolver link, observed 2026-08-04T21:08:46.124559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:46.124559Z digest=sha256:cd10582aad96ee6d2f666bac16cc27166ff5ce6ac66ee6e580e1850a26977af9

Observation a1ca7387-5199-4ab4-a207-45dd2e34278e · outbound

This paper cites Synthesizing eeg signals from event-related potential paradigms with conditional diffusion models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Synthesizing eeg signals from event-related potential paradigms with conditional diffusion models

Reference 37

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raw_fallback, observed 2026-08-04T21:09:01.616765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:46.270033Z digest=sha256:9e773894e91d6589033ed3269e086b377e64bcce0e566aa83b0ae9f6389e5ac5

Observation 9d7f649c-cdcd-4d41-a729-d59c84e89e7b · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 38

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unresolved
no resolver link, observed 2026-08-04T21:08:46.398159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:46.398159Z digest=sha256:018483b9d3e919b650cc43c0749064e8f782b091cf02681031e7d94b70733859

Observation adb7f821-1b21-4692-b762-fd1ac8dba6ed · outbound

This paper cites improved precision and recall metric for assessing generative models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis improved precision and recall metric for assessing generative models

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:01.426076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:46.517606Z digest=sha256:e79b93a57cd88e76a45fd3f2d3f37205f92f7bbc9fda7eda4fdfb3bf6dd4fdfc

Observation be0132f7-a978-4dfa-915b-f4a1d19d40ac · outbound

This paper cites Lawhern, Amelia J.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Lawhern, Amelia J

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:01.133520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:46.620120Z digest=sha256:96b175bc8798cf8f08a3a10c6fdb3f0de8f0a3333af5f15af4f1990e7a036d25

Observation 51d05442-1b0d-4fc2-89ea-30274c8148c1 · outbound

This paper cites Diffusion Models for Time Series Applications: A Survey.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Diffusion Models for Time Series Applications: A Survey

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:08:53.133030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:46.734394Z digest=sha256:c450e06d7fd80c4af1258876040dd5c285d19df80726a2b417181f6d9cab7e95

Observation 95858b4a-255a-4346-ab50-668f0346ba58 · outbound

This paper cites Flow Matching for Generative Modeling.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Flow Matching for Generative Modeling

Reference 42

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no resolver link, observed 2026-08-04T21:08:46.881367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:46.881367Z digest=sha256:55432bc3de1932d0783aa75075857d1f998055abcdfe0a1b3030338ee86f7044

Observation 50da998c-2966-4642-b617-46df01c10757 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 43

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unresolved
no resolver link, observed 2026-08-04T21:08:47.052401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:47.052401Z digest=sha256:202663b928165669ff8a07abc80d2a2ffa8129e4aea27df191d84d66ee79701b

Observation c29bf071-fc5e-459c-a09b-9121d24cf317 · outbound

This paper cites revisiting classifier two-sample tests.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis revisiting classifier two-sample tests

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:00.907959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:47.159793Z digest=sha256:2eac6a7f2cef964c57e597ceff524e0264047c3daa063bc9789beabdb130fad1

Observation b19ca65f-edba-4b85-b374-e70f0bd607e6 · outbound

This paper cites Decoupled weight decay regularization.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Decoupled weight decay regularization

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:47.299561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:47.299561Z digest=sha256:1e5aebb6653a5012cbecfaf4abd59cef863051351fee5d834276ad957c702b6b

Observation 19bba89f-fd5b-48cc-9c43-767985f7819d · outbound

This paper cites Eeg signal reconstruction using a generative adversarial network with a temporal–spatial–frequency loss.Frontiers in Neuroinformatics, 14:15, 2020.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Eeg signal reconstruction using a generative adversarial network with a temporal–spatial–frequency loss.Frontiers in Neuroinformatics, 14:15, 2020

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:00.579251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:47.472162Z digest=sha256:7fce64d3065c9ee24e5ac159b4f0f7a53a1ea34bb51ba80f2cb8bba582da1fe2

Observation 592902c0-1b3a-4f48-965a-ebc06dce2191 · outbound

This paper cites Membership Inference Attacks against Diffusion Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Membership Inference Attacks against Diffusion Models

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:08:52.881195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:47.636374Z digest=sha256:f7c59c89ab23c010801c0029ffcb71ba38b232e6711910ec88509fdd8f45bfbc

Observation 7adcf298-e268-4a5a-98aa-4d94ec34eb10 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 48

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unresolved
no resolver link, observed 2026-08-04T21:08:47.753123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:47.753123Z digest=sha256:654ae5718087490e797be7fee52fa9b9acdd72cf5bf9b1df2b987b6a7d2e9713

Observation aaeaf477-8c33-4f7c-9d1d-9c36346ceb41 · outbound

This paper cites cGANs with projection discriminator.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis cGANs with projection discriminator

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:00.240859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:47.879749Z digest=sha256:caa300917b5ee6e2a6921161cb3dde0193469c339a0ddd847e7fc2c51a06cb2a

Observation 1411fdc6-af7e-4d68-9f6e-634a375d2257 · outbound

This paper cites Mognon, J.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Mognon, J

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:09:00.046097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.005273Z digest=sha256:6808cd7e371f8118f02cccabf38c9791756b75fae84cd776175ea0cd2360b47c

Observation e16b7855-d000-465e-b7cd-fc22290f91cc · outbound

This paper cites Nayak and Sandip Bandyopadhyay.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Nayak and Sandip Bandyopadhyay

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:59.778726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.123957Z digest=sha256:a1c9c6ddaa9c7f05786c57b6867e8d52b7a323190f05ec7a9c3b2e5a2c201c66

Observation 9f453e84-7e28-43cc-b0e0-1d97681789c9 · outbound

This paper cites DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesis.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesis

Reference 52

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unresolved
no resolver link, observed 2026-08-04T21:08:48.270187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:48.270187Z digest=sha256:35e2029e1ceb3ced50b3b5fb5957ba8430208d54c2927965bf3e2bb3790de0ef

Observation 70c99606-3bec-4a33-927b-98a1ce506e9e · outbound

This paper cites improved denoising diffusion probabilistic models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis improved denoising diffusion probabilistic models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:59.552535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.384291Z digest=sha256:eadf9b8060635bafceba42c7d2c3eeb04ed7b17bb7c7aaef21fedd981c9aec89

Observation 1d7c9a37-06ed-49df-8c13-58ffb7b95c75 · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:08:59.267247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.556233Z digest=sha256:19e8993ef14333f57c248d79ca773c35b0c0e355223d020cb5f5e62c828fd3a0

Observation 187c8d59-b3c6-4c3c-acbf-8f7a0fb19faf · outbound

This paper cites Iden- tifying true brain interaction from eeg data using the imaginary part of coherency.Clinical Neurophysiology, 115(10):2292–2307, 2004.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Iden- tifying true brain interaction from eeg data using the imaginary part of coherency.Clinical Neurophysiology, 115(10):2292–2307, 2004

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:58.926862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.687041Z digest=sha256:6196495ad4ba9b23d219ef835b22641203f994d197236a5de61855d1dbbe56ff

Observation 8e7ba2ec-89b8-4701-94a1-2e1cd36915c3 · outbound

This paper cites The temple university hospital eeg data corpus.Frontiers in Neuroscience, 2016.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis The temple university hospital eeg data corpus.Frontiers in Neuroscience, 2016

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:58.717718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.822686Z digest=sha256:f1452df7a22019b83b161b312b58dcdc3dd79a0a26cea8557e16501a8819daf8

Observation e7412ad3-d147-4d97-ac6f-6344d302ef25 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Pytorch: An imperative style, high-performance deep learning library

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:58.466911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:48.954575Z digest=sha256:64b0c7ad04c402d917e5fafd38ce5e421e8a3c5f78f369af61eee54f101c1018

Observation 9c6dc1cb-a5f3-47ab-b71b-ba2aa264d988 · outbound

This paper cites Automagic: Standardized preprocessing of big eeg data.bioRxiv, page 460469, 2019.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Automagic: Standardized preprocessing of big eeg data.bioRxiv, page 460469, 2019

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:58.245282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:49.124370Z digest=sha256:9837f0a6126b107e91d5870f573df81d108d0844e33510435c03a5c5173a30d5

Observation 9c0e0371-c68a-4159-92bf-6a534d539a77 · outbound

This paper cites scalable diffusion models with transformers.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis scalable diffusion models with transformers

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:58.005406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:49.247290Z digest=sha256:e7a0b7a18bf637952105cfec966758d5d9b293f59beb4bcb996e3957d6c1e085

Observation 87675595-e9d9-4a2f-b75f-e052f99f778e · outbound

This paper cites Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:08:52.602944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:49.293361Z digest=sha256:62c67ca05fa7c46bbbb2584e5c74b43497a41f49f9949d703633124a54f863ab

Observation 4c17c761-1eae-470c-91e9-42cfce95b944 · outbound

This paper cites film: visual reasoning with a general conditioning layer.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis film: visual reasoning with a general conditioning layer

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:57.752201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:49.443782Z digest=sha256:a3a0249e7409730981e81fad754d84ee0fbb37665223dba7fca3cb812daa169e

Observation 09c1ab27-7544-4498-a498-91a10c7eb1e5 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis U-net: Convolutional networks for biomedical image segmentation

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:57.489274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:49.570541Z digest=sha256:dfd7d94297731409f65bb8d1499cfe507ddd33a192c99e70cb7679a9c9f78caa

Observation 1f1480aa-f7ed-4982-ae17-1bba4e854924 · outbound

This paper cites Falk, and Jocelyn Faubert.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Falk, and Jocelyn Faubert

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:57.219853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:49.719583Z digest=sha256:251bd6556709dec2130ff9c3fc2f85433e76bb5bba41cfdcbb8d2c53ff046db1

Observation d5ca1193-78de-417a-9d11-9b25c443c5c6 · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:49.887078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:49.887078Z digest=sha256:3ef3c458038a082eda92509ed080de36953b7a4ff041cea06d4936a217046142

Observation 8c9bf7de-7082-4f70-b548-091d91c42a16 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Progressive Distillation for Fast Sampling of Diffusion Models

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:50.037601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:50.037601Z digest=sha256:042d1a3a019ce0b89efb11dd79ea38b9cb728751b29e862b669c69029c7346df

Observation a8f2063f-1a68-4c2e-97c8-f6bc90c24fbd · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 66

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:08:56.913738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:50.142775Z digest=sha256:be3ef0af1f806a3f3d8e1bd4c0aa270f51e27a61ee4f3236398ad301e356c0e2

Observation c4658c8a-6b9d-4ff7-8a6e-077150ac737f · outbound

This paper cites McHugh, Lily Veloso, Meysam Golmoham- madi, Iyad Obeid, and Joseph Picone.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis McHugh, Lily Veloso, Meysam Golmoham- madi, Iyad Obeid, and Joseph Picone

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:56.621364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:50.277002Z digest=sha256:0a706f0107b04d686aec85b5ddf229ad3f98d6e52795f419aa8a6d91a733997c

Observation 77768c2d-564d-46ba-9f86-93650707d365 · outbound

This paper cites Denoising Diffusion Implicit Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Denoising Diffusion Implicit Models

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:50.384651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:50.384651Z digest=sha256:1d0753984d1ddc23b28e27e4fd3cf7cfed809ba9d98625cc26fbd02233e09f88

Observation e88dda69-14a3-4dc0-a549-0ba9405e71a3 · outbound

This paper cites Consistency Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Consistency Models

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:50.550315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:50.550315Z digest=sha256:14d8fa137c138a94221975e5d6c5fabee46d7153eab94bda5aeb65391b2c8692

Observation d7a5c050-296e-44ae-a8c2-25fdfe09e087 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Score-Based Generative Modeling through Stochastic Differential Equations

Reference 70

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unresolved
no resolver link, observed 2026-08-04T21:08:50.673012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:50.673012Z digest=sha256:dc49084d12add8201208224ca285ad0e91e5cf73a8fba7c4b10a9e5be373fafd

Observation dbeeb91b-66ab-4eeb-991a-b418e225c317 · outbound

This paper cites evaluation measures for synthetic time series: a taxonomy and empirical study.Journal of Big Data, 11(1):92, 2024.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis evaluation measures for synthetic time series: a taxonomy and empirical study.Journal of Big Data, 11(1):92, 2024

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:56.419107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:50.833958Z digest=sha256:904454dbd483d17d256c2decc3ec37902d7396b87da11938b2f954ac55162d9b

Observation f353af76-e3ab-47ca-a0bc-ec2b9240dcaa · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:08:56.205463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:50.981751Z digest=sha256:57f4dae101dae20d56676e0e1e6daf8ce6ffa706e2b05a67516e842eb1f0108c

Observation 7619425b-9575-4168-847c-03d3f5404041 · outbound

This paper cites EEG Synthetic Data Generation Using Probabilistic Diffusion Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis EEG Synthetic Data Generation Using Probabilistic Diffusion Models

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:51.098875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:51.098875Z digest=sha256:6e985b787630aae6b747463084b280197b3c3e06b721fb4ee1cb722b37e17548

Observation 09d90a68-9e7d-46a7-bf9f-ab86b58b003b · outbound

This paper cites EEG artifact removal—state-of-the-art and guidelines.Journal of Neural Engineering, 12(3):031001, jun 2015.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis EEG artifact removal—state-of-the-art and guidelines.Journal of Neural Engineering, 12(3):031001, jun 2015

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:55.947351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:51.232585Z digest=sha256:e635c46abf45838355f046d937a4a9b56cfa6e2edf1fb1e4200646300b799a7d

Observation e10566c5-024a-4209-a5ac-e2c92d0addc9 · outbound

This paper cites Visualizing data using t-SNE.Journal of Machine Learning Research, 9:2579–2605, 2008.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Visualizing data using t-SNE.Journal of Machine Learning Research, 9:2579–2605, 2008

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:51.327770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:51.327770Z digest=sha256:8ae073f2bad1ce6cfa06bf95b5d11ecaf2f73c762d05d270a4ad922c64150e6c

Observation 0eb77cbe-34c1-4d19-a9fe-78b38e4c1758 · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 76

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:08:55.602062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:51.457118Z digest=sha256:211c14bf4e5db6995324d58ec09f0169a1ffa62fa51d55a70f1c7cef1d581698

Observation 480713c6-1b4d-4c51-9ca8-06489dca881a · outbound

This paper cites an unresolved cited work.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:08:55.264918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:51.650167Z digest=sha256:1f871c7aaff3912a5c8b7afd2c5b372d0fe16abe9170409d661ec73a0679c090

Observation 85397f6b-0f53-4196-bc2c-3cbef2dc929a · outbound

This paper cites Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:51.803520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:51.803520Z digest=sha256:ff00d0a774fc2c83a123348231e6bb8cf692bd82e726485dd89d5a5f8b6d1c19

Observation 5ae0a92b-efef-4df0-b91d-d82072d54c0a · outbound

This paper cites Automatic classification of artifactual ica-components for artifact removal in eeg signals.Behavioral and Brain Functions, 7(30):1–15, 2011.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Automatic classification of artifactual ica-components for artifact removal in eeg signals.Behavioral and Brain Functions, 7(30):1–15, 2011

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:55.011196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:51.902793Z digest=sha256:b4180a4f2d26a2c76d23cfb093142205bf85c682b2b66712f4f697481e29b608

Observation 1bc28804-3aab-4bdd-a262-5fdadf0d19fd · outbound

This paper cites parallel wavegan: a fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis parallel wavegan: a fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:08:54.735647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:08:52.026791Z digest=sha256:7e55655c73fe73a34b3056d10ae8d6fe1c1bd1963250c76fd8be29711277ff89

Observation 35fd8d9b-2b59-47f7-b8e4-a468ec85d5f2 · outbound

This paper cites Time-series generative adversarial networks.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Time-series generative adversarial networks

Reference 81

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unresolved
no resolver link, observed 2026-08-04T21:08:52.122037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:52.122037Z digest=sha256:8824d92247c419b22a905d736ec62c79c08fe1fb64422d274d36fcb50f506745

Observation 45246a3c-33ce-49f4-b9e3-4b66065d183a · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models.

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis Adding Conditional Control to Text-to-Image Diffusion Models

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-04T21:08:52.234225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:08:52.234225Z digest=sha256:6b2bb57c2f629e5b944c50fb7db5a6fccba77a9c7f5beefc541995e11c2f2df8

Pith citing papers

No inbound Pith citation observations are available.