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Paper Citation Record · LEDGER

An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2410.04133.

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

pith.paper-citation-record.v1
2410.04133 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:22:20.328751Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 517e46fc-830f-48c0-85b5-67cf4aff0161 · inbound

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models cites this paper.

Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T20:22:20.328751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:22:20.328751Z digest=sha256:29868d1f733fb7e555119ab16139bac203acec5de904e6f835dccf241e58f5d3

Observation 32aa029a-47ed-4adb-99e3-5790a3f65d4b · inbound

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI cites this paper.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-03T15:01:44.119989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:01:44.119989Z digest=sha256:bc0e483449b6624f61e91564dcde0fef3f22e8269b0445fc34a8b264ac12421d

Observation 67a2e0af-917d-4111-9b4f-d31c62ff4e9e · inbound

ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook cites this paper.

ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 157

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:28:14.212709Z

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=2026-05-13T20:23:15.138933Z digest=sha256:2b08806c756e948ac1a91e1335d38d099821e84f88af8da38d4e99eb93b43f13

Observation a3df7aae-7933-4206-9fb5-0b7f15e78485 · inbound

Towards Real-Time ECG and EMG Modeling on $\mu$NPUs cites this paper.

Towards Real-Time ECG and EMG Modeling on $\mu$NPUs An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:01:13.533392Z

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=2026-05-10T05:57:26.793743Z digest=sha256:badd04ce6f686408fa591981112666657ad7a0ab271fd74d0273745d2b7abfe0

Observation d50589f3-edea-4b82-b8d2-70e21cb2b31d · inbound

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning cites this paper.

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:26:06.103563Z

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=2026-05-09T20:06:15.659662Z digest=sha256:0a84a4b779d51419712523216eb075acf5e550d9d8ad207770a1d6a1205d79c3

Observation 05d2357b-a241-4152-bd08-bd177d6a181c · inbound

EduGage: Methods and Dataset for Sensor-Based Momentary Assessment of Engagement in Self-Guided Video Learning cites this paper.

EduGage: Methods and Dataset for Sensor-Based Momentary Assessment of Engagement in Self-Guided Video Learning An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:16:11.649505Z

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=2026-05-09T17:55:14.450023Z digest=sha256:98e9cb60b9f2c99503b48f6fe2d7abeb700bf63ba977abc1e6ebba3fa706ac5e

Observation ea199911-c12e-4465-8fd1-c1f07a73ae00 · inbound

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons cites this paper.

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:07:47.106949Z

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=2026-05-19T21:03:38.354134Z digest=sha256:8935d76d2492496978efe72bf11467b2243f0c0b136a721db38b32e47a7d3c1c

Observation c3f198a9-4c79-4531-a495-6bec6ffc2335 · inbound

How Do Electrocardiogram Models Scale? cites this paper.

How Do Electrocardiogram Models Scale? An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:48:19.706585Z

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=2026-05-20T13:46:30.968131Z digest=sha256:5fce156bce35ae00facad085baf93b5e00036e6c89c80e126eb931708a9b0bb1

Observation ad478263-220f-4448-9196-1454d09e9044 · inbound

VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data cites this paper.

VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T08:23:15.962712Z

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=2026-06-29T07:24:32.497634Z digest=sha256:13d775ad67a126e259436514ae1da8944c50ba5e982ce082ce1e2211451e2bec

Observation 862873e3-1b9c-44d0-995a-2356a2a8734d · inbound

Learning Cardiac Latent Representations in Vectorcardiogram Space cites this paper.

Learning Cardiac Latent Representations in Vectorcardiogram Space An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-06-28T23:42:49.692283Z

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=2026-06-28T23:37:15.894948Z digest=sha256:8dc01f1eea25c79b1b3edae04d64c614289a05d34e721d90433ae2db71b8455a

Observation 379d1944-fd58-446d-aca9-6490877854ee · inbound

Cross-Modal Contrastive Learning of ECG and Angiography Representations for Severe Stenosis Classification cites this paper.

Cross-Modal Contrastive Learning of ECG and Angiography Representations for Severe Stenosis Classification An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T13:54:43.561128Z

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=2026-06-30T13:52:03.511902Z digest=sha256:aa5793104f5c5a7e5ea32abfb6a07dab6e4a8cbb65d18c876367c9ac4c81a527

Observation d71bb6ce-fd38-41bb-a8ac-88a8210c7e2f · inbound

Do ECG Foundation Models Transfer to Rare Cardiac Diseases? Evidence from Brugada Syndrome Detection cites this paper.

Do ECG Foundation Models Transfer to Rare Cardiac Diseases? Evidence from Brugada Syndrome Detection An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-12T05:29:44.415283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T05:29:44.415283Z digest=sha256:6a798a9238c14a51c46623713f46b6e2e1a1d18926c1ea8b7a6e72b11b696267

Observation e2cc778c-2110-4eff-8538-c06ae4e4e454 · inbound

LSTrans: Efficient Knowledge Transfer for Lightweight and Automated ECG Classification cites this paper.

LSTrans: Efficient Knowledge Transfer for Lightweight and Automated ECG Classification An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-14T09:18:25.640217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T09:18:25.640217Z digest=sha256:2ad83105f4c2eb27752543bbcfa8bc04dae374a4061b4dcb5b99d65be48dd7f0