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Paper Citation Record · LEDGER

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator

As of 12 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2509.10491.

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

pith.paper-citation-record.v1
2509.10491 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:18:03.516212Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T20:41:10.528667Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

  • verified exact2
  • verified fuzzy13
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 903a3f86-d7b9-4c42-a0f8-db2eca1a4f11 · outbound

This paper cites Deep generative models as the probability transformation functions.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Deep generative models as the probability transformation functions

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:18:03.913924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:01.525748Z digest=sha256:d7a26a080b8df76793b4c3322a6af2941be548ba15f9ec5aa7496c789a39dae0

Observation 0fc682e2-8afe-412f-9773-c5ad16a79505 · outbound

This paper cites Generation of ecg signals from a reaction-diffusion model spatially discretized.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Generation of ecg signals from a reaction-diffusion model spatially discretized

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.475351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:01.615719Z digest=sha256:0d6e8a6eefcd75af7f864eabfcbf0dd7a2cf12da649aae38449de5e159470d2d

Observation a2e7a5eb-0b06-4e2f-a26e-7257ce54217d · outbound

This paper cites Adversarial Audio Synthesis.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Adversarial Audio Synthesis

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T13:18:01.760962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:18:01.760962Z digest=sha256:67be261d2c88374d487aba6984a9c12eabc8ecbd62e12b5aa9a18d23df2746fb

Observation d30b1aea-cafe-4be6-8549-5c466d1ccc02 · outbound

This paper cites Deepfake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Deepfake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.460747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:01.917184Z digest=sha256:aaa6fcecbb515d337003ec5e1a9dd01202c75ecd4939c4857488e52c67ab8216

Observation 5516dcf2-d9d2-4093-ac85-a4c6b26ad868 · outbound

This paper cites Synsiggan: Generative adversarial networks for synthetic biomedical signal generation.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Synsiggan: Generative adversarial networks for synthetic biomedical signal generation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.446485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.104618Z digest=sha256:71868c4c86e66de606c43891610288310ce5a9bf3c2d1f7f8f4e719e8bb082d9

Observation 7f3e8528-3d1f-41bb-9db7-5f9234832cb8 · outbound

This paper cites Generative adversarial network with transformer generator for boosting ecg classification.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Generative adversarial network with transformer generator for boosting ecg classification

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.432827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.231298Z digest=sha256:6e25c75c7c3af7910706ae94cd3d5ebc9458a9338abb7049e547924755df6720

Observation 881d9a1a-9ec9-45da-a15a-b4693b38cca3 · outbound

This paper cites Diffusion-based conditional ecg generation with structured state space models.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Diffusion-based conditional ecg generation with structured state space models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.418075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.321559Z digest=sha256:b6e8e06e010267b70a078a1c72764c33d56f12bb294dfdf7bb6720ab141a1f23

Observation 7f0359eb-8f78-4cac-86b0-a2f014d51c95 · outbound

This paper cites Diffecg: A versatile probabilistic diffusion model for ecg signals synthesis.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Diffecg: A versatile probabilistic diffusion model for ecg signals synthesis

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.402943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.448079Z digest=sha256:62b889012c3e28a81984ff94c5e7f860ca63e97922bd09efc380c434c910a9ef

Observation b261f997-b4b4-4d96-a89d-945074d74273 · outbound

This paper cites Ecg synthesis via diffusion-based state space augmented transformer.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Ecg synthesis via diffusion-based state space augmented transformer

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.388603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.579955Z digest=sha256:e448df0099340100b9c02d5ebc6b0abfc26b091ed98d127a50e2558c57a7743b

Observation 7ff6e859-fc44-42ae-a66f-e841225b080e · outbound

This paper cites Biodiffusion: A versatile diffusion model for biomedical signal synthesis.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Biodiffusion: A versatile diffusion model for biomedical signal synthesis

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.375016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.662425Z digest=sha256:a185aa47b1ca7097f4107cb99e4a48864f09bf668e586cb001fbdc7d569833f1

Observation 0e98d66c-4b78-468c-b11f-f3d6df57340e · outbound

This paper cites Vaeeg: Variational auto-encoder for extracting eeg representation.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Vaeeg: Variational auto-encoder for extracting eeg representation

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.361244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.754930Z digest=sha256:8b5128334e50970b7f0e039f9f98bddfc583a0cb3abf9037d6fada628bd2bc6a

Observation 2bdc1f30-c79b-4052-90ab-1a02a0532483 · outbound

This paper cites Simgans: Simulator-based generative adversarial networks for ecg synthesis to improve deep ecg classification.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Simgans: Simulator-based generative adversarial networks for ecg synthesis to improve deep ecg classification

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.346578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.857751Z digest=sha256:9ddbb3170722d161bc4dcda7dce4e70d46027b665f036a994c66f6da8005338a

Observation 456daad7-25ef-42f2-a242-55f3698096d8 · outbound

This paper cites PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:18:03.720044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:02.942402Z digest=sha256:5807d4602216fba2325a24edb71ab4b112e9c858d333b007775d1a0dcebfd953

Observation edb24d87-ebc8-4f44-ab5f-7ca8bfe4adde · outbound

This paper cites Ptb-xl, a large publicly available electrocardiography dataset.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Ptb-xl, a large publicly available electrocardiography dataset

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T13:18:03.012819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:18:03.012819Z digest=sha256:84fd99096b749586493470d6000b976a3e5ed4adf7557278c0e1e25c1b7fc0d3

Observation bf9e8518-c410-45d3-91aa-e1e7897c9746 · outbound

This paper cites Flow Matching for Generative Modeling.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Flow Matching for Generative Modeling

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T13:18:03.137130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:18:03.137130Z digest=sha256:c48023d0be20fdbd2244858664ce9a0a444beede8b3e84db1c84da4be4563193

Observation f957712e-6915-4934-a64f-3865087777ee · outbound

This paper cites Spectral similarity measure using frequency spectrum for hyperspectral image classification.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Spectral similarity measure using frequency spectrum for hyperspectral image classification

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.322908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:03.218435Z digest=sha256:8ba0638c0b5735411a6c8c4f1d6e3beb398911d4b13452d9162f6f923dc5b9d0

Observation 0dc92ef2-1368-40e2-8d27-28b129d04d90 · outbound

This paper cites Borgwardt, Malte J.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Borgwardt, Malte J

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.294761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:03.305592Z digest=sha256:2a2d30de860edc126df8dea6bf06f0b8f32f1eeb610213f34ba9401989fc95cf

Observation 6baa167f-d9eb-4aed-8dc4-5d152906cdc6 · outbound

This paper cites Calibrated reliable regression using maximum mean discrepancy.

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator Calibrated reliable regression using maximum mean discrepancy

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:18:04.162927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T13:18:03.433475Z digest=sha256:a4ded8029999471e9b76486911fbad120635da853b33d3813e572a39dec3c9bf

Observation ae206484-86bc-441a-b233-487359a62677 · outbound

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

FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T13:18:03.516212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:18:03.516212Z digest=sha256:017b5c65145d0d477dc82678c57ef0ae622ad1f357c686dc3e772486f32ab129

Pith citing papers

Observation 68b38d1c-c105-45db-b0e3-3c3105363082 · inbound

Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series cites this paper.

Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series FlowECG: Using Flow Matching to Create a More Efficient ECG Signal Generator

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-11T20:41:10.528667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T20:41:10.528667Z digest=sha256:f5d63a1a9aabf18ed5e7ab6567d4394c9e0b82aa1962dc1ae9953b6a28848c38