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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.20253.

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

pith.paper-citation-record.v1
2407.20253 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:36:01.784794Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-04T21:08:54.289483Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation aaca0127-5c9a-4bee-acca-b6523a1f0a37 · inbound

Transformer-based EEG Decoding: A Survey cites this paper.

Transformer-based EEG Decoding: A Survey Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models

Reference 106

Resolution
unresolved
no resolver link, observed 2026-08-06T20:36:01.784794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:36:01.784794Z digest=sha256:1dcfc544697a0c29923a1a9a081fd73b752928508c7a564484a74da6f34c3f60

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

ArtifactGen: Benchmarking WGAN-GP vs Diffusion for Label-Aware EEG Artifact Synthesis cites this paper.

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:08:42.808698Z digest=sha256:035e5e5c6a4ac1e680f437258a72971495b516642317561e83025f2c7f732bc1