{"as_of":"2026-08-07T16:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1a590d8fb0df1a37a02d963070d0bb245af726964456840757561755484f2136","coverage":[{"denominator":72,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":72,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T16:11:42.527299Z","state":"measured"},{"denominator":72,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":72,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2604.10117/citation-record","integrity":"/paper/2604.10117/integrity","json":"/paper/2604.10117/citation-record.json","paper":"/paper/2604.10117"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2014.688212","doi":"10.1109/ieeestd.2014.6882122","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"IEEE Standard for Wearable Cuffless Blood Pressure Measuring Devices.IEEE Std 1708-2014(2014), 1–38","venue":null,"work_id":"bf245258-46cd-4408-a8cd-596888375e44","year":2014},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:fdea4dcb1857bdf1e4dc4ad937835a42d448a9178e6a1cf3eb81056b8f219062","observation_id":"263b3d1b-f097-498b-be57-869a79c75adc","resolution":{"observed_at":"2026-05-10T16:15:34.556815Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s21062167","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Cymberknop, and Ricardo L","venue":"Sensors","work_id":"44807eb9-fd2f-4791-aa3f-8b919b87091f","year":2021},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6f1b0c82107aa0c0e76e6437c30d36fc2a125232b057458f4867914862822394","observation_id":"be269058-8060-46b4-84c6-be993e27e9bc","resolution":{"observed_at":"2026-05-10T16:15:34.583803Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1097/mbp.0000000000000639","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Almeida, Josep Sola, Bruce S","venue":"Blood Pressure Monitoring","work_id":"bc200f42-bc60-4de1-a63d-5baae0b9d95b","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:7927137deee099944385fdd51d445b235e3eac55ac8781dc875213a14064d820","observation_id":"dd313f17-5596-4547-bfe5-4e1b108ccb73","resolution":{"observed_at":"2026-05-10T16:15:34.538974Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.104782","doi":"10.1016/j.bspc.2023.104782","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Biomedical Signal Processing and Control","work_id":"38699bd1-0999-4e34-8c47-d46fc746212b","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:a6e957c2d86f9f02a500a6da3be478bff98aa89fd9779b5422c3cbdd0193fc47","observation_id":"43b5936d-2402-4fa4-a065-3c29b53a57b3","resolution":{"observed_at":"2026-05-10T16:15:34.545016Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Almeida, Meritxell Cortés, David Perruchoud, Jérémy Alexandre, Pascale Vermare, Josep Sola, Jay Shah, Luisa Marques, and Cyril Pellaton","venue":null,"work_id":"83fabb8c-a25d-4847-91f5-bffeba7d8bf8","year":null},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:0456563bb0c6d1ab10981908ecb35257fc73983e621e7ef023daaf576013a724","observation_id":"c9df2e2e-590c-49ce-b541-95773b7369a4","resolution":{"observed_at":"2026-05-17T16:34:58.396668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41440-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"doi:10.1038/s41440- 023-01258-2","venue":null,"work_id":"d50cec16-bab4-41e0-892c-b1efed54c7e4","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6275f7c4a8e1859ca6b2c1c11da3115c77c302d4251a9a3abf50da15a366dc4b","observation_id":"238e1845-f0a7-4b4f-aaaa-027af46d279e","resolution":{"observed_at":"2026-05-10T16:15:34.565794Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.15352","last_updated":"2025-02-18T05:44:29Z","snapshot_observed_at":"2026-08-03T10:14:56.786950Z","submitted_at":"2024-04-15T00:36:33Z","title":"TransfoRhythm: A Transformer Architecture Conductive to Blood Pressure Estimation via Solo PPG Signal Capturing","version":2},"cited_work":{"arxiv_id":"2404.15352","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.15352","snapshot_observed_at":"2026-07-03T07:17:44.647953Z","title":"Kent, and Arash Mohammadi","venue":null,"work_id":"f2982916-0a1c-4c7d-9aee-5a8bfc0dd86f","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/2404.15352","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:ba771a478e285987fd7999ec066a9c2a94ee3c7dbeea5ec31592b282c7c7aff0","observation_id":"9ebe9682-b666-4fb8-ab0f-945ccd2978f6","resolution":{"observed_at":"2026-05-11T09:11:01.464186Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3587256","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"ACM Transactions on Computing for Healthcare","work_id":"3a68b6fb-85fe-4e8f-affa-2d35a8e44d89","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:ae1ea342b8d9bad93dadccb7fdde22805dd5ff93a9d3effe8d41ff6baab83cf8","observation_id":"1d5036ee-5b32-4871-9e7c-6c23e4a71ae9","resolution":{"observed_at":"2026-05-10T16:15:34.561787Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17860","last_updated":"2024-12-20T13:25:50Z","snapshot_observed_at":"2026-07-06T20:12:22.686355Z","submitted_at":"2024-12-20T13:25:50Z","title":"EnhancePPG: Improving PPG-based Heart Rate Estimation with Self-Supervision and Augmentation","version":1},"cited_work":{"arxiv_id":"2412.17860","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.17860","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"0e8bea02-8351-4e25-8c34-ba165662199d","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/2412.17860","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:fd3b8a2393d850813ccd65ae11735547eaba213e528808ba36c8a08d87ebbc95","observation_id":"498886d2-3e38-4a6e-9238-e1aee8176aa8","resolution":{"observed_at":"2026-05-11T09:11:01.473004Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"4109.2020","doi":"10.1109/embc44109.2020.9175593","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Alberto Borghese, and Simona Ferrante","venue":null,"work_id":"04690523-c6bc-4bc9-8762-68e53e0f86b8","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:f66c69b010860999fe80d804ced80aaf6440a1d2db5fb471ca1c3d6582e242b5","observation_id":"36a350b3-f3a0-4d71-925f-730df74ad90e","resolution":{"observed_at":"2026-05-10T16:15:34.541171Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"7902.339403","doi":"10.1145/3387902.3394038","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":null,"work_id":"bc21ca36-94b7-4efe-bb39-a47d8edc4896","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:90916ad7a40d1c417ae905b1cfc405bf061baaf421e46213a7f99875f40f5932","observation_id":"9d7579cd-12cd-4e86-8649-f2088a5012b4","resolution":{"observed_at":"2026-05-10T16:15:34.537239Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1083.2024","doi":"10.1109/biocas61083.2024.10798236","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Online Epileptic Seizure Detection in Long-Term iEEG Recordings Using Mixed- Signal Neuromorphic Circuits","venue":null,"work_id":"3e4d564c-1664-40c6-afa6-97ce845a4807","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6543238d1de9d6b8c88b2f414883f3d395113b05dd80d1c4ca0aa196875e266a","observation_id":"266f4198-8f82-4232-9c0f-16d909f14665","resolution":{"observed_at":"2026-05-10T16:15:34.564188Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.07127","last_updated":"2021-03-19T15:08:55Z","snapshot_observed_at":"2026-07-06T09:47:38.903599Z","submitted_at":"2020-08-17T07:30:54Z","title":"DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs","version":3},"cited_work":{"arxiv_id":"2008.07127","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2008.07127","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"fb8fb79d-51c9-46b2-a82c-eb89940bfad2","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/2008.07127","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:56aedaace1c87ab0022c8e9519411e940d6d4d98c1a9582c4076222b487219b4","observation_id":"973683e3-4d86-42a7-ae8e-8cf41f634b93","resolution":{"observed_at":"2026-05-11T09:11:01.443490Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.12932","last_updated":"2022-03-25T15:54:59Z","snapshot_observed_at":"2026-07-06T12:51:55.231850Z","submitted_at":"2022-03-24T08:37:26Z","title":"Bioformers: Embedding Transformers for Ultra-Low Power sEMG-based Gesture Recognition","version":2},"cited_work":{"arxiv_id":"2203.12932","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.12932","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"3067453e-6c2c-4a4a-8a5a-2799da398a2b","year":2022},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/2203.12932","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:9e9c2a3fd0c325d6dacf29e6ee24d09f187a1d1b94eea6a0805a7594ef1dfb24","observation_id":"757d3217-6b1c-40e9-b8e8-492ffe5aea40","resolution":{"observed_at":"2026-05-11T09:11:01.423647Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3487910","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"ACM Transactions on Computing for Healthcare","work_id":"3b3c9fe7-14ca-4cbf-a5cf-059ee95c2f54","year":2022},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:b07fa7c6b782ccc984ef218118c1ae3e77f8f2e77c59b248cada290c2df55cae","observation_id":"3446a451-aae6-41db-9343-d45d3e5be794","resolution":{"observed_at":"2026-05-10T16:15:34.549975Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.312201","doi":"10.1109/tbcas.2021.3122017","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"https://doi.org/10.1109/tem.2021.3122012, http://dx.doi.org/10.1109/ TEM.2021.3122012","venue":"IEEE Transactions on Biomedical Circuits and Systems","work_id":"06237561-055d-414d-9b15-884e6e4941a6","year":2021},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:af57e34a7fc7f800873e3a7fe67f7758a382b240adceb47ccb9dafa0e662edd4","observation_id":"d14bb19b-e7c2-4e6b-8114-07834d5ab10c","resolution":{"observed_at":"2026-05-10T16:15:34.532952Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05795","last_updated":"2020-04-13T07:02:23Z","snapshot_observed_at":"2026-07-06T09:11:53.623802Z","submitted_at":"2020-04-13T07:02:23Z","title":"Rethinking Differentiable Search for Mixed-Precision Neural Networks","version":1},"cited_work":{"arxiv_id":"2004.05795","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2004.05795","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"961e7aa0-2529-43ad-a50b-87a421e42d7a","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/2004.05795","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:e91e0ca998400055bb7604eaebfd5c8e54088cc4af2ae174f62277b2b7e24d01","observation_id":"df1e2156-cee5-461e-9fa9-0ebd9fa22103","resolution":{"observed_at":"2026-05-11T09:11:01.362706Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s21010156","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Thompson","venue":"Sensors","work_id":"8bbfcb3d-851a-4c76-ae4a-502b09b21c60","year":2021},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:c2652cd68b03fce25bee58175e10efa74042a25bb42e52d7d7d655f22e78b375","observation_id":"bf4da119-4276-4c17-8a7e-bc25620b856b","resolution":{"observed_at":"2026-05-10T16:15:34.542700Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.compbiomed.202","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d087ccfd-4b30-469e-ae87-2b0372aa14b2","year":2021},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:d0ad219330acf4d5e522c93798caf84b802e81441c97dc96790fcb0614c72178","observation_id":"7c4d9cf0-0783-4fb7-a5d6-1a918eb997ee","resolution":{"observed_at":"2026-05-10T16:15:34.534854Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s25010040","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Sensors","work_id":"31d66da8-3a64-4897-a40c-03e49c03e947","year":2025},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:29193d644ea9d93815f05d21a93be85719939ff97b21e5d7a0101f0466b1f795","observation_id":"af2ff29a-e7c0-425f-8bd3-28ec8aefca5a","resolution":{"observed_at":"2026-05-10T16:15:34.569018Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.06085","last_updated":"2018-07-17T07:33:19Z","snapshot_observed_at":"2026-07-06T06:39:21.688392Z","submitted_at":"2018-05-16T01:19:43Z","title":"PACT: Parameterized Clipping Activation for Quantized Neural Networks","version":2},"cited_work":{"arxiv_id":"1805.06085","doi":"10.48550/arxiv.1805.06085","metadata_source":"pith","pith_arxiv_id":"1805.06085","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"PACT: Parameterized Clipping Activation for Quantized Neural Networks","venue":"cs.CV","work_id":"ab8da7fe-9ff3-44e6-9132-11d17ceef8c2","year":2018},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/1805.06085","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:659856f9a55b6b1620faa2987782b956debed2220b3a5e90956c25382fe2023a","observation_id":"978283ef-5ffb-4ccc-867b-b5007beadd28","resolution":{"observed_at":"2026-05-11T09:11:01.417295Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.328445","doi":"10.1109/access.2023.3284458","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"IEEE Access","work_id":"0f4fb65d-b2a2-487b-b794-8ef408c44cc9","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:d4cc64528a9e9ce45b021f51b3c912fe7347634e175ea20356630e9511120bdc","observation_id":"cfaf5be8-04c7-4b12-9a9f-d2f849e42688","resolution":{"observed_at":"2026-05-10T16:15:34.573001Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/embc","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T03:34:32.269018Z","title":"Kyriacou","venue":null,"work_id":"38b404f7-f2a0-4fa1-8c11-614ebbd5e19f","year":2012},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:47d8bedc7d9b6f6ee20dd86130bfbed361404ef48e33f0634195e49fc38bc43e","observation_id":"52d61913-aea4-485e-b3e8-9e0dfe266966","resolution":{"observed_at":"2026-05-10T16:15:34.551653Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2019.103392","doi":"10.1016/j.advwatres.2019.103392","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Advances in Water Resources","work_id":"5fff8be2-7168-46ac-be9f-32afe3401d26","year":2019},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6b00ae285a82b7299add662e28ddac8d8903402e4a43517dfd6076d8b792be4d","observation_id":"2591a21b-09f4-492d-badb-067ba2cdb0de","resolution":{"observed_at":"2026-05-10T16:15:34.554103Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1161/hypertensionaha.119.14240","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Fuchs and Paul K","venue":"Hypertension","work_id":"a637e235-64b4-436a-ab39-5f25394e4e39","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:0f54edec677ad6d0a0721b069a85fd6bc32192788480063fb26e3ecb9ca2b672","observation_id":"49a06722-8bb2-4dff-ac8f-f27d58c8c31b","resolution":{"observed_at":"2026-05-10T16:15:34.570623Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.11263","last_updated":"2019-08-29T14:42:39Z","snapshot_observed_at":"2026-08-06T13:59:23.098374Z","submitted_at":"2019-08-29T14:42:39Z","title":"PULP-NN: Accelerating Quantized Neural Networks on Parallel Ultra-Low-Power RISC-V Processors","version":1},"cited_work":{"arxiv_id":"1908.11263","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1908.11263","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"18b30349-cbd8-4d94-8197-4ee965c77451","year":2019},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/1908.11263","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:a2b622c73335b7839480afab20d73629a2543be845f213ac95acfad75f14f86a","observation_id":"8f43b9dc-0979-4091-9949-8a873382417d","resolution":{"observed_at":"2026-05-11T09:11:01.428876Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.2196/13048","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"JMIR Cardio","work_id":"de50a2c4-ee86-4825-a4dc-ea87d838d9db","year":2019},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:12049190d17e86dea354f00c15e5331d051348e4b8acb9a3fe7ddb3995bc59d6","observation_id":"35cc4796-6011-4850-9b12-f0eff2c23aba","resolution":{"observed_at":"2026-05-10T16:15:34.577149Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41597-023-02020-6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Scientific Data","work_id":"bdea5cc1-7ba3-4e28-974c-a993f504681f","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:25238434b9c5d32e05fdb98fa40dd1823a7ca0ae74d4af1bee6c8f628e6b34aa","observation_id":"4f387267-5552-400a-951e-eb9907b0e14b","resolution":{"observed_at":"2026-05-10T16:15:34.567470Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2016.75162","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T03:34:32.429817Z","title":null,"venue":null,"work_id":"93e9dc9a-ebe2-4b75-bbc6-551cb9bc23e0","year":2016},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:728f987d03b60b262f2e4c347e943d64d4856ef7ce7b516c9cc702990e350a6b","observation_id":"0fe45900-9999-4cc8-8666-2a09aef9b507","resolution":{"observed_at":"2026-05-11T09:11:01.448785Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam","venue":null,"work_id":"3292b46c-eaae-4482-810d-abc156d89b46","year":null},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:d4ade2f106de77b57e2e803af4dff7bc6982d888513d88cd7f23a98773404781","observation_id":"15aeb52d-2939-42a2-bdce-4c22c09f8408","resolution":{"observed_at":"2026-05-17T16:34:58.409404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1704.04861","last_updated":"2017-04-17T03:57:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-04-17T03:57:34Z","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","version":1},"cited_work":{"arxiv_id":"1704.04861","doi":"10.48550/arxiv.1704.04861","metadata_source":"pith","pith_arxiv_id":"1704.04861","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","venue":"cs.CV","work_id":"3870239a-c950-4625-bf33-c4f902d14175","year":2017},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/1704.04861","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:21982e7fb0121aad33a946bc297d0a32c01f3715a7a9d3f69a1de3abe69df64e","observation_id":"c5fa16a0-ace4-4ad3-96ad-44dfeb2a00e3","resolution":{"observed_at":"2026-05-11T09:11:01.370382Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.103404","doi":"10.1016/j.bspc.2021.103404","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Biomedical Signal Processing and Control","work_id":"83e9fa69-03c4-4eb4-8984-20b8969a3b71","year":2022},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:cf35220bc05aeeba59d56ffe3bb62b11659aea4f20a7036a9f401e666708bdaf","observation_id":"0054c180-83d4-4c17-af60-113a7e2cc819","resolution":{"observed_at":"2026-05-10T16:15:34.582110Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Access 27/03/2025","venue":null,"work_id":"71574b4d-a2e8-45d4-a935-8cbca67a51a3","year":2025},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:f798fa0b9a7aec501aeb89e519a0e007d9ecdda7af68724218a80416b53ded8a","observation_id":"fdee2567-83b5-48bb-a34c-d8b828b578c7","resolution":{"observed_at":"2026-05-17T16:34:58.405169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11892-019-1161-2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Current Diabetes Reports","work_id":"3cb2d0c9-0a41-4a8f-bac3-b767471e1aa1","year":2019},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:c54a426d9248935fc49e5fbf6decce2b526d80ec733f309dc1d33721a4bb0093","observation_id":"6e739d58-25b2-4057-9bdc-a10ae16c7ba3","resolution":{"observed_at":"2026-05-10T16:15:34.546605Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09488","last_updated":"2023-07-18T07:11:14Z","snapshot_observed_at":"2026-08-06T00:43:59.749460Z","submitted_at":"2023-07-18T07:11:14Z","title":"PLiNIO: A User-Friendly Library of Gradient-based Methods for Complexity-aware DNN Optimization","version":1},"cited_work":{"arxiv_id":"2307.09488","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.09488","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Jahier Pagliari, M","venue":null,"work_id":"585c37ac-8cfc-4865-84f3-4a55c083a698","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/2307.09488","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:c177461a2285a9b7cc001b4846c054d9d3ea4eb313a13e76db84c48dd3e2922e","observation_id":"0a43ab01-0e3f-41e5-9ba4-bd233ba064cb","resolution":{"observed_at":"2026-05-11T09:11:01.377532Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/sdata.2016.35;subjmeta","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Johnson, Tom J","venue":null,"work_id":"82a992a8-1246-4ebd-a3c3-30821d4d2d8d","year":2016},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:d40d6c8a8ce7a796e3a3b6eb054353174bc9f1b19ef22c87d526d4081ddcadc4","observation_id":"05d31de8-162a-4c48-bfe9-1160de748abd","resolution":{"observed_at":"2026-05-10T16:15:34.548389Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2014.690819","doi":"10.1109/aicera.2014.6908199","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":null,"work_id":"76520e17-fe3d-464f-8ee1-4df41e2640ca","year":2014},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:37d6bdacc9170cbb26da450567205ee697da06480e83e196ee2c444e6e7f0da6","observation_id":"2930f6ad-3d17-4508-b4df-e67ef7171b1f","resolution":{"observed_at":"2026-05-10T16:15:34.575300Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3699512","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"ACM Transactions on Design Automation of Electronic Systems","work_id":"a8695c26-2f19-4e2b-8c7b-37434f879ee4","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:9221671daf53629f7b0f8a689928a77e9b9da76b18c2fca28447fa6273a97157","observation_id":"e2754b48-fe55-4102-a6a9-786b56ef9a0a","resolution":{"observed_at":"2026-05-10T16:15:34.560135Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/iscas.20","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d99b9dd4-52ea-4fe0-9d8a-f43da4a90f52","year":2015},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:efd5838cb862c1f707ac12f8defbeb42f62ba960a30ea655cca38ebc84855086","observation_id":"9462addb-5e95-4b97-b06d-29c3c18bba47","resolution":{"observed_at":"2026-05-10T16:15:34.558436Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2016.258090","doi":"10.1109/tbme.2016.2580904","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"2017 , journal =","venue":"IEEE Transactions on Biomedical Engineering","work_id":"352ecde3-b16d-4757-bd4d-6eb5b6f7346b","year":2017},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:2559fd5a434c77f9667631ea879139b1d303a93a551da8f09f19994b4e452b6f","observation_id":"dda23dca-37d9-4992-9dd8-1c835ab80629","resolution":{"observed_at":"2026-05-10T16:15:34.579621Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.30402","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"7ed9c9f5-cc29-43c8-9011-c5ac04382f77","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:360cb46ac3415dd4460e05c376b27d5c8143ab72e2682f91b0f153242982425d","observation_id":"9423cba4-29c0-4a17-830d-8604abb2f5a0","resolution":{"observed_at":"2026-05-11T09:11:01.397826Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.341794","doi":"10.1109/access.2024.3417940","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"IEEE Access","work_id":"d74fd522-e66d-4405-8593-382caacef849","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:496608682d201c8b3502ad22365c95f74716a7c57b8b3dcaf81fefb49b362fd0","observation_id":"4f58a5f3-591f-44d4-bda7-5f206f1e3857","resolution":{"observed_at":"2026-05-10T16:15:34.586243Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.103488","doi":"10.1016/j.cose.2023.103488","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Computers & Security","work_id":"92aa0130-17ad-4866-ba69-704a83fa16cf","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:9c3832227dbaec1cf6fa447e624c3c45e501fd13ad1eb1e7cd70fd670edc9aa6","observation_id":"0a9bd292-a369-4977-a329-a0cebb27659a","resolution":{"observed_at":"2026-05-10T16:15:34.631768Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s20195606","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Sensors","work_id":"966ff168-e72d-47e3-a126-343aa1ddb646","year":2020},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:89428996db39a1b734a49665ec91130a503fd4f34f00e1a43a4fbb0331b96894","observation_id":"ef7e5ac0-410c-4aca-9ad1-43bf4a85b3cc","resolution":{"observed_at":"2026-05-10T16:15:34.610839Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/sdata.2018.20","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Scientific Data","work_id":"70e65304-9153-4962-bb83-0ec6782c685d","year":2018},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:4c729991ff6e4af3bab3f58b10bbfe8797900d8295b72bf09259b70863ef1b2a","observation_id":"dbdd1308-c315-43f2-aec5-1d9e895e70c1","resolution":{"observed_at":"2026-05-10T16:15:34.587791Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2025.107585","doi":"10.1016/j.bspc.2025.107585","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Biomedical Signal Processing and Control","work_id":"3051e442-2bbf-4cac-b0bf-e80bca2fc419","year":2025},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:b9418816d0d31069faaab3b469403f3d57090635089d21b9b4405b9a882d205b","observation_id":"c2262454-e5e8-4bff-9fea-b64d54fc3d88","resolution":{"observed_at":"2026-05-10T16:15:34.635778Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"6164.2021","doi":"10.1109/embc46164.2021.9629489","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Design and Performance Evaluation of a Novel Vascular Robotic System for Complex Percutaneous Coronary Interventions","venue":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","work_id":"449ae59a-851c-425c-b020-634cb983f0a7","year":2021},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6d62dc29d8888784132ca45b32e0b3bb3aa16a12d7aef4d7f46bd957d469f672","observation_id":"1b8d3f65-3962-442e-8238-56ab7ad27f13","resolution":{"observed_at":"2026-05-10T16:15:34.605166Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.09055","last_updated":"2019-04-23T06:29:32Z","snapshot_observed_at":"2026-08-01T17:05:53.501765Z","submitted_at":"2018-06-24T00:06:13Z","title":"DARTS: Differentiable Architecture Search","version":2},"cited_work":{"arxiv_id":"1806.09055","doi":null,"metadata_source":"pith","pith_arxiv_id":"1806.09055","snapshot_observed_at":"2026-07-10T21:27:35.708872Z","title":"DARTS: Differentiable Architecture Search","venue":"cs.LG","work_id":"2f7f6e44-42e7-498e-a68f-a01e092a8903","year":2018},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/1806.09055","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:fe3232379f40819c807786f594d055c70db0df4a4c3954f3051afcf3dc3538f1","observation_id":"85978ccb-cb34-41ce-9d79-1a0cce8cf0e8","resolution":{"observed_at":"2026-05-11T09:11:01.436844Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"5a61d3fd-c38d-436c-b6b2-d1feb09227b1","year":2006},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:881018289aa71cbd0abcf6abcfb58fc683e31b0aa78e58c7a6c1e1bfe5b75cfe","observation_id":"26d7dab4-d8b5-43e7-aba6-027fea1e38b8","resolution":{"observed_at":"2026-05-17T16:34:58.412848Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/jcm7100316","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Journal of Clinical Medicine","work_id":"bb71b339-708d-4801-b669-9e819f6138f3","year":2018},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:ba4f046019a1b2bbf4025dd624cbd17be7ac54c31058315da227932d2c1092a9","observation_id":"2edf35a0-fdec-4601-9025-a3261bf6ed98","resolution":{"observed_at":"2026-05-10T16:15:34.591251Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2017.00231","doi":"10.3389/fmed.2017.00231","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Meidert and Bernd Saugel","venue":"Frontiers in Medicine","work_id":"a30c077f-4d5b-47bf-8c44-0b435e5de636","year":2017},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:5569b2d3f652b91c3604bd632d54293d6b989df6cfbb1722f50e0c8babf175cb","observation_id":"66247487-e530-4c12-978b-bad9c30138b5","resolution":{"observed_at":"2026-05-10T16:15:34.624743Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/tc.2024","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Design of a universal decoder model based on DNA winner-takes-all neural net- works","venue":null,"work_id":"3534a1e0-3391-4f8e-8058-163b66e2bf8f","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:66b10de339a2c8354953cb08e7846085fc8e17acf8dd333396cc6489f9991b85","observation_id":"d3be3f7a-14b6-4bf4-bac3-3054f7d6ae4d","resolution":{"observed_at":"2026-05-10T16:15:34.589700Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2015.244195","doi":"10.1109/tbme.2015.2441951","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Inan, Lalit K","venue":"IEEE Transactions on Biomedical Engineering","work_id":"408ebea8-d3f6-4349-b832-83a6c13e727f","year":2015},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:1b31d345129699b3eb6e6d5b735065b3ae271bdcb4ad6fe54cc956f11bd57194","observation_id":"5f5203ce-8da5-4e49-b764-51bbd5854223","resolution":{"observed_at":"2026-05-10T16:15:34.593556Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1136/bmj.i4482","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"BMJ","work_id":"b14f92a0-9085-41d6-a9a0-e9b546c6e136","year":2016},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:4922a2038e60b5e2cd214fdf94181c9c542689ec15ea6a67bc3b8bd28df702f0","observation_id":"268d40f3-3711-48da-86f2-662c672828e5","resolution":{"observed_at":"2026-05-10T16:15:34.633426Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/bioengineering10040400","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Bioengineering","work_id":"985ac543-2323-4d8d-a5eb-e27899c4a8e6","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:d5725f3f12178e94903f566f6f31047a1b6edcedf1d71baff9b123bab4fb7cc0","observation_id":"376238fd-c56b-4e6c-ba33-9b738fa2bcec","resolution":{"observed_at":"2026-05-10T16:15:34.617788Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2953.2021","doi":"10.1109/icmla52953.2021.00157","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"In 2021 20th IEEE International Conference on Machine Learning and Applications","venue":"2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)","work_id":"bdabc024-b18f-492c-9688-6159b5275c13","year":2021},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:004c830a8b10bfea1ae6f2662407ab41c2abed08ea984178e66a9e64678c3a13","observation_id":"f05aa7f0-618c-48da-9226-d90855025da5","resolution":{"observed_at":"2026-05-10T16:15:34.627415Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1505.04597","last_updated":"2015-05-18T11:28:37Z","snapshot_observed_at":"2026-08-06T11:05:16.105361Z","submitted_at":"2015-05-18T11:28:37Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":"1505.04597","doi":"10.1007/978-3-662-06400-9_9","metadata_source":"pith","pith_arxiv_id":"1505.04597","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","venue":"cs.CV","work_id":"5c6b13d6-e704-4bf4-9df7-3a3a4d3b6950","year":2015},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/1505.04597","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6b83d0026f1f4da2a0d3ebbf3283f1fbeea10df95f4b96bbaf5f74ed396abcb6","observation_id":"bc5f611c-bf08-49cc-b6d1-a3fbe6811852","resolution":{"observed_at":"2026-05-11T09:11:01.390800Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2022.321275","doi":"10.1109/tim.2022.3212750","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"IEEE Transactions on Instrumentation and Measurement","work_id":"990d93e4-a752-4838-89df-5801df4a2588","year":2022},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:87df1195eedef09e81db8a848b73f9a0aea51d9f7cb91eee46b8f5908911ce7f","observation_id":"2faafe94-a721-4630-a14b-6d7aa9b54a93","resolution":{"observed_at":"2026-05-10T16:15:34.596098Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2002.116685","doi":"10.1109/cic.2002.1166854","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Shagun Sodhani, Amy Zhang, and Joelle Pineau","venue":"Computers in cardiology","work_id":"3125f67a-d585-414d-8612-cae3231316a6","year":2002},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:06f1cd32fdabc4c6eb966298487de946fba0dcf0915ca7adfb4a7418d68f1c93","observation_id":"c75a0a65-bd13-4e4a-ba4f-bdfebdb5167d","resolution":{"observed_at":"2026-05-10T16:15:34.616033Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Access 16/05/2024","venue":null,"work_id":"50ae578f-44ea-4658-a72a-74a2243fc0f3","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:78c7640206de276e7963a4feee4870e7de8628d82be4f5ca109cf4ed990206f5","observation_id":"db4aa9c8-aee4-48a5-b609-fb20ea3393c1","resolution":{"observed_at":"2026-05-17T16:34:58.419528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1083.2024","doi":"10.1109/biocas61083.2024.10798236","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Online Epileptic Seizure Detection in Long-Term iEEG Recordings Using Mixed- Signal Neuromorphic Circuits","venue":null,"work_id":"3e4d564c-1664-40c6-afa6-97ce845a4807","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:54c0654186009c43749c0970b1e7ee6755facf6e9b0534b8d9fdb707507a31a1","observation_id":"dc67e393-b346-41bf-8b2f-908420f6b8c9","resolution":{"observed_at":"2026-05-10T16:15:34.602828Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.03185","last_updated":"2018-06-08T14:29:08Z","snapshot_observed_at":"2026-07-06T06:43:47.008039Z","submitted_at":"2018-06-08T14:29:08Z","title":"Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation","version":1},"cited_work":{"arxiv_id":"1806.03185","doi":null,"metadata_source":"pith","pith_arxiv_id":"1806.03185","snapshot_observed_at":"2026-07-04T05:49:36.657790Z","title":"Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation","venue":"cs.SD","work_id":"dd35a7b9-ad8f-4170-a530-b284205c2df9","year":2018},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"cited_paper":"/paper/1806.03185","citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:6d0a63685e0ebbb6453fe3ba19bd6cba70a230c826c7bee7c4e06cf1133737ca","observation_id":"31d498da-df42-4814-9bf1-02c8424b243e","resolution":{"observed_at":"2026-05-11T09:11:01.458342Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"5776.357774","doi":"10.1145/3555776.3577743","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Multi-Robot Expansive Planning and Trajectory Evaluation for Tracking and Localization of Marine Life,","venue":null,"work_id":"5c987a27-90d5-49df-828e-3fea1f0670bf","year":2023},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:7f1161156f335204278bbe2684d2e51aa220ab9b093012247656f7dc9ede32d5","observation_id":"f2395d44-0d07-41b9-8dc1-ccd515d54b58","resolution":{"observed_at":"2026-05-10T16:15:34.607562Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Access 16/05/2024","venue":null,"work_id":"2d5a48b5-b0ea-4ba7-b40e-f094d876fb96","year":2024},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:af79c683ebdcf8d765855d95fdce7b2ff6136a8e9219e6adbdcfbef197ff59d1","observation_id":"9366d067-b5f1-4ab6-be01-a62906673834","resolution":{"observed_at":"2026-05-17T16:34:58.416106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.106741","doi":"10.1016/j.bspc.2024.106741","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A paralleled cnn and transformer network for ppg-based cuff-less blood pressure estimation","venue":"Biomedical Signal Processing and Control","work_id":"02db3e09-f41c-45e6-8f55-902651c2e44d","year":2025},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:ae9807383eaed1b42f1c47f028ca9a8f8d52fc8ac980996abd4a32086e5845a1","observation_id":"05c481e6-649e-4054-8f99-03cb7e8baa1d","resolution":{"observed_at":"2026-05-10T16:15:34.622182Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-21T23:23:08.185334+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-21T23:23:08.185334+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:54:34.179538Z","title":"Gomez, Łukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":"e1d86123-00cd-4902-9ba8-202969bd4af2","year":2017},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:504c2183de9383d53ebdbd8496d65fd907b50847e2bfad8ff3955d559f7f17ce","observation_id":"a58c4469-39c2-46a1-bf0b-716c2cb5ff6d","resolution":{"observed_at":"2026-05-17T16:34:58.400677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/bjaceaccp/mkm022","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Continuing Education in Anaesthesia Critical Care & Pain","work_id":"67785da0-6d48-4b12-b69f-33071117ca7d","year":2007},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:8efcbfc69796a471389f5ba540c6c68ed5a613e9caf1928c44a9016022f8edaf","observation_id":"782b2109-062d-422d-870e-7c28f79438bb","resolution":{"observed_at":"2026-05-10T16:15:34.597998Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1161/01.hyp.21.4.504","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"White, Alan S","venue":"Hypertension","work_id":"4fb7d24e-f346-43d7-b723-7964b576ae2c","year":1993},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:b7c3a304a00d9dad91b4419198ab3b547334fb344d42e482359d33155875a583","observation_id":"7066b8d8-20ce-4840-921a-91e8e1aa79fa","resolution":{"observed_at":"2026-05-10T16:15:34.619654Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"8229.2022","doi":"10.1109/embc48229.2022.9870914","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Analysis of Brain-Heart Interactions in newborns with and without seizures using the Convergent Cross Mapping approach","venue":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","work_id":"39df8798-ff63-4847-a011-730eab7c585e","year":2022},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:15e7c881419a3d6134c2191a0e9cf58eb7d325b10bd59ee6f544b58a119de518","observation_id":"c64ea813-f99d-4691-bd35-b3a1cade001c","resolution":{"observed_at":"2026-05-10T16:15:34.600424Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s40820-025-02003-9","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Nano-Micro Letters","work_id":"f3419c4b-6740-4bbf-950f-649e69c524b4","year":2026},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:962f849ff5fb6fa100686d7a0ab7995f490066df1fa37eb815ec7980f5c49897","observation_id":"7c9aacc3-6a50-4d31-b43f-7a6ac218d8f9","resolution":{"observed_at":"2026-05-10T16:15:34.609216Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2025.353578","doi":"10.1109/jbhi.2025.3535788","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Time-series large language models: A systematic review of state-of-the-art.IEEE Access, 13:30235–30261, 2025","venue":"IEEE Journal of Biomedical and Health Informatics","work_id":"79fc6c07-4e5f-479f-8c8b-e394d1378291","year":2025},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:ab26d372a814c0f7e64525d412286061f49a825c31365782af2b8721cbd94726","observation_id":"a9337b13-9b7e-4a69-a6d9-f0ab15bbe498","resolution":{"observed_at":"2026-05-10T16:15:34.613292Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/electronics11091378","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Electronics","work_id":"9af20870-a64b-4050-a580-f40c91716b24","year":2022},"citing_paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-10T16:11:42.527299Z"},"links":{"citing_paper":"/paper/2604.10117"},"observation_digest":"sha256:1af4688c993d44610f1e4d3e08c379df9638cdc559bd0fe699acbea9942efdd8","observation_id":"6f8c1c41-224e-44e5-af22-38b4063507f6","resolution":{"observed_at":"2026-05-10T16:15:34.629095Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.10117","last_updated":"2026-04-25T09:23:05Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-31T17:38:33.524572Z","submitted_at":"2026-04-11T09:21:18Z","title":"End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables"},"reference_resolution":{"displayed":72,"state_counts":{"malformed_identifier":5,"metadata_mismatch":9,"parse_uncertain":0,"unresolved":1,"verified_exact":51,"verified_fuzzy":6},"total_outbound_references":72},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2604.10117."}