{"as_of":"2026-08-09T12:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f738df23e622f3d28436aaabec1e2fae80b157ad756a68d8dd5573dd735a1b5a","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:27:14.528124Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-28T23:42:49.688208Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-08-07T14:27:14.528124Z","title":"Reading your heart: Learning ecg words and sentences via pre-training ecg language model, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.18847","last_updated":"2025-05-24T19:43:15Z","snapshot_observed_at":"2026-08-09T06:42:27.544144Z","submitted_at":"2025-05-24T19:43:15Z","title":"Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T14:27:14.528124Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2505.18847"},"observation_digest":"sha256:6b9ad12b7b9abfbc5f762bda131849c8257fd24a7937c4290e2c72cd689acbb5","observation_id":"24182e24-02c9-4a57-bd64-4a975681d50f","resolution":{"observed_at":"2026-08-07T14:27:14.528124Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":"2502.10707","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-06-28T23:42:49.688208Z","title":"Reading Your Heart: Learning ECG words and sentences via pre-training ECG language model.arXiv preprint arXiv:2502.10707","venue":null,"work_id":"f4e56ee0-b581-4dfd-851d-19def11341c4","year":2025},"citing_paper":{"arxiv_id":"2506.05831","last_updated":"2026-04-07T10:06:53Z","snapshot_observed_at":"2026-08-02T20:29:58.309302Z","submitted_at":"2025-06-06T07:56:41Z","title":"HeartcareGPT: A Unified Multimodal ECG Suite for Dual Signal-Image Modeling and Understanding","version":4},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-19T10:44:01.880405Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2506.05831"},"observation_digest":"sha256:54aa52006a38e28b92c1aaebd29f2c53fe43be5084291171264f469cff24b546","observation_id":"2f70c417-5c92-466c-b731-2b2ddf77774e","resolution":{"observed_at":"2026-05-19T10:47:15.075862Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-08-04T15:45:10.072023Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.18588","last_updated":"2026-06-17T07:22:49Z","snapshot_observed_at":"2026-08-09T04:58:38.955294Z","submitted_at":"2025-09-23T03:15:53Z","title":"UniECG: Understanding and Generating ECG in One Unified Model","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T15:45:10.072023Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2509.18588"},"observation_digest":"sha256:90006dec91469eac3727cc1ec80e12448464aac56156b8d05414ddfed602a0ce","observation_id":"20e38cff-19cf-4137-ad0d-a3ee28b9d9a3","resolution":{"observed_at":"2026-08-04T15:45:10.072023Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":"2502.10707","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-06-28T23:42:49.688208Z","title":"Reading Your Heart: Learning ECG words and sentences via pre-training ECG language model.arXiv preprint arXiv:2502.10707","venue":null,"work_id":"f4e56ee0-b581-4dfd-851d-19def11341c4","year":2025},"citing_paper":{"arxiv_id":"2605.03462","last_updated":"2026-05-24T17:28:39Z","snapshot_observed_at":"2026-07-06T23:16:25.301792Z","submitted_at":"2026-05-05T07:50:00Z","title":"From Muscle Bursts to Motor Intent: Self-Supervised Token Modeling for Heterogeneous EMG","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-07T17:15:32.796215Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2605.03462"},"observation_digest":"sha256:e1db5a5e0e4ca34a7d6125b774f0fa28d0b97eea5d9f316e59f210f41fb23065","observation_id":"7ef6ec29-439d-47f7-b288-af9a13472d47","resolution":{"observed_at":"2026-05-12T11:01:30.724239Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":"2502.10707","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-06-28T23:42:49.688208Z","title":"Reading Your Heart: Learning ECG words and sentences via pre-training ECG language model.arXiv preprint arXiv:2502.10707","venue":null,"work_id":"f4e56ee0-b581-4dfd-851d-19def11341c4","year":2025},"citing_paper":{"arxiv_id":"2605.03462","last_updated":"2026-05-24T17:28:39Z","snapshot_observed_at":"2026-07-06T23:16:25.301792Z","submitted_at":"2026-05-05T07:50:00Z","title":"From Muscle Bursts to Motor Intent: Self-Supervised Token Modeling for Heterogeneous EMG","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-21T00:16:00.572880Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2605.03462"},"observation_digest":"sha256:4057f457801b4ac1f9f83d8e08489993172a5275667f2fd242ab6581c5192935","observation_id":"0ec71d50-c802-4b1c-8c96-fdeafacdda70","resolution":{"observed_at":"2026-05-21T00:19:16.754146Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":"2502.10707","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-06-28T23:42:49.688208Z","title":"Reading Your Heart: Learning ECG words and sentences via pre-training ECG language model.arXiv preprint arXiv:2502.10707","venue":null,"work_id":"f4e56ee0-b581-4dfd-851d-19def11341c4","year":2025},"citing_paper":{"arxiv_id":"2605.17276","last_updated":"2026-05-17T05:53:35Z","snapshot_observed_at":"2026-07-06T23:28:16.927009Z","submitted_at":"2026-05-17T05:53:35Z","title":"How Do Electrocardiogram Models Scale?","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-20T13:46:30.968131Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2605.17276"},"observation_digest":"sha256:543936f47583b91b89e4bbd37650429bb2e20fc19bca418a2a72307f353f5005","observation_id":"293679ba-a4ac-445e-9468-64b893d13966","resolution":{"observed_at":"2026-05-20T13:48:19.677359Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":"2502.10707","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-06-28T23:42:49.688208Z","title":"Reading Your Heart: Learning ECG words and sentences via pre-training ECG language model.arXiv preprint arXiv:2502.10707","venue":null,"work_id":"f4e56ee0-b581-4dfd-851d-19def11341c4","year":2025},"citing_paper":{"arxiv_id":"2605.31249","last_updated":"2026-05-29T12:48:12Z","snapshot_observed_at":"2026-08-01T10:14:02.823731Z","submitted_at":"2026-05-29T12:48:12Z","title":"Learning Cardiac Latent Representations in Vectorcardiogram Space","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-28T23:37:15.894948Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2605.31249"},"observation_digest":"sha256:a26e7151038ea1a96993ff4ea4f752170b7c653fc22c9717670f3d5932b82440","observation_id":"c2fe5309-b207-4cf9-b492-8e16a37671cd","resolution":{"observed_at":"2026-06-28T23:42:49.689569Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-07-31T11:54:42.184585Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24553","last_updated":"2026-07-27T15:28:02Z","snapshot_observed_at":"2026-08-07T14:05:41.957110Z","submitted_at":"2026-07-27T15:28:02Z","title":"EchoBridge: Long-Tail-Aware ECG-Echocardiography Text Alignment for Echocardiography-Derived Cardiac Findings","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-31T11:54:42.184585Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2607.24553"},"observation_digest":"sha256:3f97428ff72589498a4c726554dfe61d1207e58ca3cc24d8a4f34b0eed6279fe","observation_id":"20e5ec0d-bfce-4533-86b4-60a9a28563be","resolution":{"observed_at":"2026-07-31T11:54:42.184585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.10707","snapshot_observed_at":"2026-08-05T14:45:50.482842Z","title":"arXiv preprint arXiv:2502.10707 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.03690","last_updated":"2026-08-04T13:58:10Z","snapshot_observed_at":"2026-08-09T03:49:57.503125Z","submitted_at":"2026-08-04T13:58:10Z","title":"LAEF: A Lead-Agnostic ECG Foundation Model Towards Point-of-Care Diagnostics","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-05T14:45:50.482842Z"},"links":{"cited_paper":"/paper/2502.10707","citing_paper":"/paper/2608.03690"},"observation_digest":"sha256:02687a02fe3b8f67201bb71dfcb670caced78aaa12f9afedfeaccb4cc59b734e","observation_id":"b73b007d-06ce-44ab-ac28-69f771c7e9d3","resolution":{"observed_at":"2026-08-05T14:45:50.482842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.10707/citation-record","integrity":"/paper/2502.10707/integrity","json":"/paper/2502.10707/citation-record.json","paper":"/paper/2502.10707"},"outbound":[],"paper":{"arxiv_id":"2502.10707","last_updated":"2025-02-15T07:40:57Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T18:16:14.766548Z","submitted_at":"2025-02-15T07:40:57Z","title":"Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2502.10707."}