{"as_of":"2026-08-10T09:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c854129c210f6b332ab438b5609448e480267f1cd12644dcc3d5e7729c057322","coverage":[{"denominator":69,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":69,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:04:06.545949Z","state":"measured"},{"denominator":86,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":86,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":17,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T21:02:32.792477Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-02T20:21:17.308424Z","title":"Sensorlm: Learning the language of wearable sensors.arXiv preprint arXiv:2506.09108, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.23605","last_updated":"2026-07-01T00:30:58Z","snapshot_observed_at":"2026-08-09T20:05:44.804827Z","submitted_at":"2026-02-27T02:15:59Z","title":"SleepLM: Natural-Language Intelligence for Human Sleep","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-02T20:21:17.308424Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2602.23605"},"observation_digest":"sha256:74bdf4c15a1033d7e6c8673c34ab87e3c674e77505d7e55f4b5b566e5eccec89","observation_id":"667a697f-fc0d-4696-8794-836621bd871d","resolution":{"observed_at":"2026-08-02T20:21:17.308424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-02T20:21:02.521974Z","title":"Sensorlm: Learning the language of wearable sensors.arXiv preprint arXiv:2506.09108, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.00190","last_updated":"2026-07-05T13:20:41Z","snapshot_observed_at":"2026-08-08T16:40:37.481622Z","submitted_at":"2026-02-27T02:14:56Z","title":"OSF: On Pre-training and Scaling of Sleep Foundation Models","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-02T20:21:02.521974Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2603.00190"},"observation_digest":"sha256:1f199ed1d06141ff81c30726c2250cb055cee975618979d411f3b18029b20397","observation_id":"fde12a8a-7dad-439e-81d7-1b36fb92d6fe","resolution":{"observed_at":"2026-08-02T20:21:02.521974Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2603.03331","last_updated":"2026-05-07T11:19:22Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-10T18:46:03Z","title":"PulseLM: A Foundation Dataset and Benchmark for PPG-Text Learning","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-16T02:19:57.346471Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2603.03331"},"observation_digest":"sha256:6af8ce682b78a7cfa5fb02b55e743a8095fadd573b48c470b5edf13b5c624226","observation_id":"e86cd5f7-88d2-4ac7-bfa7-af71ed6c1116","resolution":{"observed_at":"2026-05-16T02:20:30.248828Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-02T21:02:32.792477Z","title":"Sensorlm: Learning the language of wearable sensors.arXiv preprint arXiv:2506.09108, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.06638","last_updated":"2026-06-27T22:21:54Z","snapshot_observed_at":"2026-08-09T20:14:22.957573Z","submitted_at":"2026-02-25T05:23:23Z","title":"HEARTS: Benchmarking LLM Reasoning on Health Time Series","version":3},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-02T21:02:32.792477Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2603.06638"},"observation_digest":"sha256:8ef36b0a62ed5ace6072b06c0efa710d23065cbbd47c01c3a1fed5a75a03e2aa","observation_id":"4c1a15b9-4a31-4f12-8581-461054788d7a","resolution":{"observed_at":"2026-08-02T21:02:32.792477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2604.02711","last_updated":"2026-04-08T23:13:03Z","snapshot_observed_at":"2026-08-04T09:42:48.573822Z","submitted_at":"2026-04-03T04:09:47Z","title":"Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook","version":2},"reference_index":174,"source":"pdf_text","source_observed_at":"2026-05-13T18:48:40.813486Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2604.02711"},"observation_digest":"sha256:7e8794d02269068a764faa0b974f3aa7d41414f141198c3723bf041b738e742e","observation_id":"37b65bcc-4509-4da4-bc39-df39b31e2166","resolution":{"observed_at":"2026-05-13T18:53:08.607818Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2604.10172","last_updated":"2026-04-11T11:41:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-11T11:41:11Z","title":"Wearable AI in the Era of Large Sensor Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-10T16:35:36.541995Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2604.10172"},"observation_digest":"sha256:c8a03283914f3a1023b8be2ace9a12ff251675eca80bf7ae2d8a4af307ff1814","observation_id":"f8491492-1453-40d4-9ea7-2fd467ae5a5c","resolution":{"observed_at":"2026-05-11T08:30:58.046285Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2604.10183","last_updated":"2026-04-11T12:32:55Z","snapshot_observed_at":"2026-07-06T22:58:51.931478Z","submitted_at":"2026-04-11T12:32:55Z","title":"RF-LEGO: Modularized Signal Processing-Deep Learning Co-Design for RF Sensing via Deep Unrolling","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-10T15:41:13.555266Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2604.10183"},"observation_digest":"sha256:e09b85c9f1f85e43f3f74819cec629e49c0037edbd86a05017d110ee4d183944","observation_id":"45017c9d-2938-41f0-9dce-1edf8acc32da","resolution":{"observed_at":"2026-05-11T10:01:03.635763Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2604.18058","last_updated":"2026-05-01T19:19:41Z","snapshot_observed_at":"2026-07-06T23:04:59.629739Z","submitted_at":"2026-04-20T10:26:54Z","title":"Sonata: A Hybrid World Model for Inertial Kinematics under Clinical Data Scarcity","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T04:36:51.588539Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2604.18058"},"observation_digest":"sha256:fcadf8937484b6f25a595252eb8dddf9f4ac357eab222c7199d3db53e3d45618","observation_id":"bf99b226-76a6-4a84-ae58-c75d41e01de7","resolution":{"observed_at":"2026-05-10T12:10:23.219826Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2604.21926","last_updated":"2026-04-23T17:59:16Z","snapshot_observed_at":"2026-08-03T03:34:11.234757Z","submitted_at":"2026-04-23T17:59:16Z","title":"Seeing Without Eyes: 4D Human-Scene Understanding from Wearable IMUs","version":1},"reference_index":117,"source":"pdf_text","source_observed_at":"2026-05-09T21:59:00.442135Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2604.21926"},"observation_digest":"sha256:2daa4ca511b2d374f2efb39784b1b4ae38546fff9296ce965345253fea92bb78","observation_id":"49019b28-dd24-4bd0-926e-dc49de74f4c0","resolution":{"observed_at":"2026-05-11T14:21:07.166416Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2605.04791","last_updated":"2026-05-07T08:26:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-06T11:41:31Z","title":"OpenWatch: A Multimodal Benchmark for Hand Gesture Recognition on Smartwatches","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-08T16:29:42.915942Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2605.04791"},"observation_digest":"sha256:b47b9314b19dcabd3d2b180cc64e62fa878ee8575af3bc6d43ad31c7d5986f6a","observation_id":"4a45e9a4-a41f-4233-a577-a6bcaca8c07a","resolution":{"observed_at":"2026-05-11T18:11:05.790520Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2605.21295","last_updated":"2026-05-20T15:25:46Z","snapshot_observed_at":"2026-07-06T23:31:46.877766Z","submitted_at":"2026-05-20T15:25:46Z","title":"TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-21T06:09:44.172188Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2605.21295"},"observation_digest":"sha256:a5eea934fa8f5b997771245b401527208da26f8ceec6ebe672a87c7d03a6bc98","observation_id":"eb6748bd-42a0-41dd-89b1-0ca762604ec1","resolution":{"observed_at":"2026-05-21T06:13:59.419231Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2605.23938","last_updated":"2026-04-28T04:59:03Z","snapshot_observed_at":"2026-08-06T01:48:49.871981Z","submitted_at":"2026-04-28T04:59:03Z","title":"Authority Inversion in LLM-Mediated Ubiquitous Systems: When Models Trust Users Over Sensors","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-01T09:20:01.288953Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2605.23938"},"observation_digest":"sha256:4f37bc8bebcce449e2e757fe6320971bb500beaa5c7a52e909cee8a5a9f470ad","observation_id":"507639b7-5d30-468b-a09e-2e4c0e701d23","resolution":{"observed_at":"2026-07-01T09:25:40.010419Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2606.00174","last_updated":"2026-05-29T13:47:00Z","snapshot_observed_at":"2026-08-06T07:43:11.842599Z","submitted_at":"2026-05-29T13:47:00Z","title":"MyoSem: Aligning Electromyography to Natural-Language Action Semantics for Hand Action Understanding","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-28T22:40:49.525450Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2606.00174"},"observation_digest":"sha256:909df815f53264a0795b291d28f120b613b84833c34f85d96950cfd9618c4993","observation_id":"4522e0e9-3c7b-432f-80f9-bd8424711803","resolution":{"observed_at":"2026-06-28T22:42:46.346920Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2606.04019","last_updated":"2026-06-01T06:43:50Z","snapshot_observed_at":"2026-08-08T14:10:24.462615Z","submitted_at":"2026-06-01T06:43:50Z","title":"Gravity-Aware Hierarchical Routing for Lightweight SensorLLM on Human Activity Recognition","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-28T13:27:29.324307Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2606.04019"},"observation_digest":"sha256:c19de365a25e55a7caac5b5e1fcb952381fe395bac52b920cb0fe477ab4f1038","observation_id":"f9f4882a-41d8-4d5f-afaf-61b914ab1fc4","resolution":{"observed_at":"2026-07-02T00:16:25.480632Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2606.07365","last_updated":"2026-06-05T15:08:50Z","snapshot_observed_at":"2026-08-08T07:49:20.495925Z","submitted_at":"2026-06-05T15:08:50Z","title":"A robust PPG foundation model using multimodal physiological supervision","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T22:20:51.569973Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2606.07365"},"observation_digest":"sha256:bbe96a167efe9c247a9545d20a813538ae00fc41f70cdac027e9dc5ba47e459d","observation_id":"5166af54-c284-49cc-9b6a-094636e64429","resolution":{"observed_at":"2026-07-02T16:47:10.218057Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":"2506.09108","doi":"10.48550/arxiv.2506.09108","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Ali Heydari, Girish Narayanswamy, Maxwell A","venue":"ArXiv.org","work_id":"6ab2028e-c132-44c0-af69-33a610048e96","year":2025},"citing_paper":{"arxiv_id":"2606.07692","last_updated":"2026-06-05T07:07:13Z","snapshot_observed_at":"2026-07-06T23:47:19.773490Z","submitted_at":"2026-06-05T07:07:13Z","title":"BCG-FM: A Foundation Model for Ambient Cardiac Health Sensing","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T22:44:59.267252Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2606.07692"},"observation_digest":"sha256:806b5a2a6d11db917e74f4ccc133a8d9b1d4ac9c18e827b2e91321282e82ee1b","observation_id":"f1239e73-e14b-4d45-8b79-2ee0eeab6025","resolution":{"observed_at":"2026-07-02T16:27:08.961498Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09108","snapshot_observed_at":"2026-07-11T20:41:10.528667Z","title":"Sensorlm: Learning the language of wearable sensors.arXiv preprint arXiv:2506.09108, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04245","last_updated":"2026-07-05T11:45:20Z","snapshot_observed_at":"2026-08-07T01:02:19.807846Z","submitted_at":"2026-07-05T11:45:20Z","title":"Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-11T20:41:10.528667Z"},"links":{"cited_paper":"/paper/2506.09108","citing_paper":"/paper/2607.04245"},"observation_digest":"sha256:f3da81eae1f3c43848a27d30850a06cab458737b46235f440d0259b68e94a888","observation_id":"de018be8-5ed7-4b82-803e-432ee514c240","resolution":{"observed_at":"2026-07-11T20:41:10.528667Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.09108/citation-record","integrity":"/paper/2506.09108/integrity","json":"/paper/2506.09108/citation-record.json","paper":"/paper/2506.09108"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.478509Z","title":"Large-scale training of foundation models for wearable biosignals","venue":null,"work_id":"cfb5ad71-af8c-4368-9ba0-cb0501d65ae4","year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.255625Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:827c9afe49430997ab59dd1b45fc7ca054c2befc29f67e6a1de12a504874cd16","observation_id":"f8e5e55d-5999-4f20-8be1-94b4f091d969","resolution":{"observed_at":"2026-08-07T05:04:07.482437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.466475Z","title":"Masked siamese networks for label-efficient learning","venue":null,"work_id":"19076192-b09c-4221-aace-413fba569c6b","year":2022},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.259970Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:bf6503a664af1c34c1fd066b5de67a43e28168aef51155f97fd2b9179569e627","observation_id":"841cf905-06c4-4265-a54e-a5280fca9136","resolution":{"observed_at":"2026-08-07T05:04:07.470308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.264579Z","title":"Emerging properties in self-supervised vision transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.264579Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:4904bbd2db67f9c26009610d57adac80c597f28b0431b2368fa0a137af507ca9","observation_id":"212a12f2-ac58-492b-ba44-f50d301e3f7d","resolution":{"observed_at":"2026-08-07T05:04:06.264579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.445759Z","title":"Bootstrap confidence intervals: when, which, what? a practical guide for medical statisticians.Statistics in medicine, 19(9):1141–1164, 2000","venue":null,"work_id":"f842113c-283b-493c-98ad-3990b7181927","year":2000},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.268688Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:0ff22b67eb029118950536a4418bdb0340898e05485dcddfd7e952d35066ae79","observation_id":"70bf205c-eb92-485b-bdd2-62386b2d55b7","resolution":{"observed_at":"2026-08-07T05:04:07.450088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.272709Z","title":"A simple framework for contrastive learning of visual representations","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.272709Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:97fdb8ed940f531e9743cb4ce134722beac2ec9de374b95b0b77acbeecf6ded2","observation_id":"b6870797-181a-4bd6-a87f-e57c53440874","resolution":{"observed_at":"2026-08-07T05:04:06.272709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.425181Z","title":null,"venue":null,"work_id":"ed20eed4-b117-4ef4-8b72-eafa69c2cf88","year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.276729Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d10b5fc7406e1ebf7bc956bc64da5a7c7902ca5d2874e2cf1a9d8856db5f7365","observation_id":"e8c1bcd4-a48f-4f5e-aeb4-e08dc81d64fc","resolution":{"observed_at":"2026-08-07T05:04:07.429381Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06474","last_updated":"2024-06-10T17:16:49Z","snapshot_observed_at":"2026-08-10T07:53:22.080074Z","submitted_at":"2024-06-10T17:16:49Z","title":"Towards a Personal Health Large Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06474","snapshot_observed_at":"2026-08-07T05:04:06.281116Z","title":"Towards a personal health large language model.arXiv preprint arXiv:2406.06474, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.281116Z"},"links":{"cited_paper":"/paper/2406.06474","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:21755a8d53899cd95d516253a5c8583cbe6023206f1fdf0bd6b87c20c92a9fb8","observation_id":"c00a6953-028a-4d2f-b11e-4c50044c755a","resolution":{"observed_at":"2026-08-07T05:04:06.281116Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.285349Z","title":"Clap learning audio concepts from natural language supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.285349Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:79eab3a913047672a5d6ca741affdd2c5f92809287cf76f784586c4c377d1190","observation_id":"833e4c6b-99e4-4aaa-b43f-53e8dea779b3","resolution":{"observed_at":"2026-08-07T05:04:06.285349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.404693Z","title":"A visual– language foundation model for pathology image analysis using medical twitter.Nature medicine, 29(9):2307–2316, 2023","venue":null,"work_id":"a5ebcae4-3f3a-4e3c-bcd0-6288747c9574","year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.289194Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:022a101ff86d2fd37d89d3dc65b0a9790681b1e0bff70913a02e495406722f8e","observation_id":"f36479a9-99bf-489c-a1d4-145d30dff8cd","resolution":{"observed_at":"2026-08-07T05:04:07.408835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.292971Z","title":"Llasa: A multimodal llm for human activity analysis through wearable and smartphone sensors.arXiv preprint arXiv:2406.14498, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.292971Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:09236f3f88ffbe3d421a20692a4a5baff7a9d78ce03a23957769a7589c894526","observation_id":"d75d8244-0e55-4d06-9797-15064d4bbdb9","resolution":{"observed_at":"2026-08-07T05:04:06.292971Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.297198Z","title":"Neurolm: A universal multi-task foundation model for bridging the gap between language and eeg signals","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.297198Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:64b70fa858946a166e0b54879c67ba8dfdc45a066778d29f6d4d929270c216ef","observation_id":"d4f23b30-b58e-4397-a119-a9aacc04f6e0","resolution":{"observed_at":"2026-08-07T05:04:06.297198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-07T05:04:06.301364Z","title":"Scaling laws for neural language models","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.301364Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:ef7456858bc9a5f2e2f7f2933aad27d42c842a9dbd7b32fee434d28d48052e55","observation_id":"1cca1eec-897b-4f4f-9ce9-bb21355ee996","resolution":{"observed_at":"2026-08-07T05:04:06.301364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.06866","last_updated":"2024-04-27T06:20:26Z","snapshot_observed_at":"2026-07-06T17:15:01.812342Z","submitted_at":"2024-01-12T19:40:11Z","title":"Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.06866","snapshot_observed_at":"2026-08-07T05:04:06.305716Z","title":"Health-llm: Large languagemodelsforhealthpredictionviawearablesensordata","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.305716Z"},"links":{"cited_paper":"/paper/2401.06866","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:b9e63b8384af2c035ec47af372a29a0196ae96fefc11205af048c6e8d0abf25e","observation_id":"66227ad1-bd47-4750-8ae9-44025463ab82","resolution":{"observed_at":"2026-08-07T05:04:06.305716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.310092Z","title":"Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.310092Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:e355103dd8f444fed043f28704df8c99e6d2b6462d662ca480b53663e3843616","observation_id":"1890c741-c2a9-40da-817c-5eb792a19941","resolution":{"observed_at":"2026-08-07T05:04:06.310092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.375903Z","title":null,"venue":null,"work_id":"6d3af384-e5c8-42a2-996c-ba5eea4ea73f","year":2025},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.314406Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:400ec6bac4770ffa38ffefa0a9d13fd3b931d0f0dc8f89c683e5f3aa9e1d6e7f","observation_id":"fddef3b8-9f05-46f4-aad8-7bd2c13330ad","resolution":{"observed_at":"2026-08-07T05:04:07.379688Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15525","last_updated":"2023-05-24T19:25:16Z","snapshot_observed_at":"2026-07-30T22:52:51.575527Z","submitted_at":"2023-05-24T19:25:16Z","title":"Large Language Models are Few-Shot Health Learners","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15525","snapshot_observed_at":"2026-08-07T05:04:06.318531Z","title":"Large language models are few-shot health learners.arXiv preprint arXiv:2305.15525, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.318531Z"},"links":{"cited_paper":"/paper/2305.15525","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:e062437e890947d6bb390aa7c5a90244ef7c3bcece8cfe6f74d6fc6197b8a99d","observation_id":"1e12a4c2-2cb4-40ff-8f9a-7651b4f2d1a5","resolution":{"observed_at":"2026-08-07T05:04:06.318531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.09336","last_updated":"2024-07-12T15:13:16Z","snapshot_observed_at":"2026-08-03T20:03:27.384236Z","submitted_at":"2024-07-12T15:13:16Z","title":"Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.09336","snapshot_observed_at":"2026-08-07T05:04:06.324107Z","title":"Guidelines for augmentation selection in contrastive learning for time series classification.arXiv preprint arXiv:2407.09336, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.324107Z"},"links":{"cited_paper":"/paper/2407.09336","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d35665fc75499014d189277155d5ddd8df018620f10c45cf9c93821b090853d4","observation_id":"e9a37e22-0cba-491b-8d55-dd79458ea9ca","resolution":{"observed_at":"2026-08-07T05:04:06.324107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.329258Z","title":"Decoupled weight decay regularization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.329258Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:a7bee68c63b9e72844848470482f5d36c902ec9b85eb241ff39f4f2a0897a1b2","observation_id":"257360a2-7a7a-4f23-a650-dc136df5b983","resolution":{"observed_at":"2026-08-07T05:04:06.329258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.354871Z","title":"A visual-language foundation model for computational pathology.Nature Medicine, 30(3):863–874, 2024","venue":null,"work_id":"350d4931-c173-4edc-862e-ebe453090571","year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.334574Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:e0d60745d6ef88ee674cf491c2eeabf0fcfef61ca630140cce3d764fabf0cb0b","observation_id":"ef43d9db-6147-4eb8-8eb4-c2642878ec18","resolution":{"observed_at":"2026-08-07T05:04:07.358951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06464","last_updated":"2025-09-08T17:59:48Z","snapshot_observed_at":"2026-07-06T18:28:16.301122Z","submitted_at":"2024-06-10T17:00:54Z","title":"Transforming Wearable Data into Personal Health Insights using Large Language Model Agents","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06464","snapshot_observed_at":"2026-08-07T05:04:06.338535Z","title":"Transforming wearable data into health insights using large language model agents.arXiv preprint arXiv:2406.06464, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.338535Z"},"links":{"cited_paper":"/paper/2406.06464","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d854e7b5b7c039d978c8a42b9c52acf848a5e5baaf6ec41daf2aaaadc1ec6aa3","observation_id":"62483fdb-c7c3-4703-95c6-f8932b51d0ad","resolution":{"observed_at":"2026-08-07T05:04:06.338535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.343240Z","title":"Merrill, Mingtian Tan, Vinayak Gupta, Thomas Hartvigsen, and Tim Althoff","venue":null,"work_id":"295345f8-b4c1-4b87-b498-ed420749abce","year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.342889Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:cf74e3090f6cbd3e4ff87196376dea85cf8c6ce403cc26202053a393864570a9","observation_id":"1c9a3902-d555-41d6-b79d-93072e62237e","resolution":{"observed_at":"2026-08-07T05:04:07.346915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.330603Z","title":"Imu2clip: language-grounded motion sensor translation with multimodal con- trastive learning","venue":null,"work_id":"5f111cd1-18e2-42f1-99e6-a0f7cb1f4190","year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.347706Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:de3864e7de4e428f01cfd199ff31161c81d3f07045c940302543d9ceb02ccd83","observation_id":"316694e0-ce39-438b-93e6-22f8c8a282d1","resolution":{"observed_at":"2026-08-07T05:04:07.335018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.318461Z","title":"Tailor, Jacob Sunshine, Yun Liu, Tim Althoff, Shrikanth Narayanan, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak Patel, Samy Abdel-Ghaffar, and Daniel McDuff","venue":null,"work_id":"07b05ceb-df2e-4b64-a3f7-fdf84d0f37b6","year":2025},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.351562Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d8ff9c73232ab33bac5fa72e6c445c4ff6165b5bb397cef1522e12fd8ceba80d","observation_id":"1009ff39-6c54-42c7-a1f1-4a21911d4217","resolution":{"observed_at":"2026-08-07T05:04:07.322460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.355495Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.355495Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:82cb4501c4e7d04d86ce2d8efe03fc5dadf1946326a8b81aecf4621d543a7f52","observation_id":"dc687f0e-f5f5-46aa-b276-5308b7d26a1b","resolution":{"observed_at":"2026-08-07T05:04:06.355495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.297837Z","title":"Fitbit-based interventions for healthy lifestyle outcomes: systematic review and meta-analysis.Journal of medical Internet research, 22(10):e23954, 2020","venue":null,"work_id":"4979c533-87b1-4c78-b446-55b786dfaf50","year":2020},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.359462Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:90a3642a55ef048c055974779c35695f809f2d04185bd8ccdfa2c001e1978761","observation_id":"26b661ad-89d4-4ada-8f94-fc04a91279e2","resolution":{"observed_at":"2026-08-07T05:04:07.301815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.285717Z","title":"Data augmentation for learning predictive models on eeg: a systematic comparison.Journal of Neural Engineering, 19(6):066020, 2022","venue":null,"work_id":"d6fbc94b-3703-4e11-b499-b3ce598cade3","year":2022},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.363420Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:694d2c89b4f7fce9535a0751269103213a2d16c92d02b8d22d3552abcce036fa","observation_id":"0fbbd9b9-6b72-4947-8381-941505f82cd9","resolution":{"observed_at":"2026-08-07T05:04:07.289672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.11542","last_updated":"2021-02-11T05:41:43Z","snapshot_observed_at":"2026-08-07T12:17:21.212932Z","submitted_at":"2020-11-23T16:55:22Z","title":"Exploring Contrastive Learning in Human Activity Recognition for Healthcare","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.11542","snapshot_observed_at":"2026-08-07T05:04:06.367328Z","title":"Exploringcontrastive learning in human activity recognition for healthcare.arXiv preprint arXiv:2011.11542, 2020","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.367328Z"},"links":{"cited_paper":"/paper/2011.11542","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:c00e8d9332c03b3284947e7d69f5a852a237768956af223bcc6f97f01a281b81","observation_id":"210b99c5-8e4c-40f9-9e74-11bea6c54fb8","resolution":{"observed_at":"2026-08-07T05:04:06.367328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-07T05:04:06.371520Z","title":"Gemini: a family of highly capable multimodal models.arXiv preprint arXiv:2312.11805, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.371520Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:85625ae4ae9a604c5be7f0492bf057cf5686bd859ab33c6211fe2fe64e945fc3","observation_id":"5975283e-a5de-430b-a0c8-93ad42b058e9","resolution":{"observed_at":"2026-08-07T05:04:06.371520Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.19786","last_updated":"2025-03-25T15:52:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-25T15:52:34Z","title":"Gemma 3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.19786","snapshot_observed_at":"2026-08-07T05:04:06.375309Z","title":"Gemma 3 technical report","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.375309Z"},"links":{"cited_paper":"/paper/2503.19786","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:80c7bc7833418b2b5c20172b80650dec48563fddf7974f958a71b4a1be4a4d72","observation_id":"58596b3b-c450-4eaa-bfa0-ea648fefcfba","resolution":{"observed_at":"2026-08-07T05:04:06.375309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.273404Z","title":"SleepFM: Multi-modal representation learning for sleep across brain activity, ECG and respiratory signals","venue":null,"work_id":"ea3eb829-b05b-43dc-b8fe-3190040ef4b2","year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.379440Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d5d4979f8c68a307a01c258dacb4de8586b78d266b601f12229ec0e1c1120030","observation_id":"983645f6-18d3-42d1-a744-82bccbffaf9b","resolution":{"observed_at":"2026-08-07T05:04:07.277412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-07T05:04:06.383217Z","title":"Llama 2: Open foundation and fine-tuned chat models.arXiv preprint arXiv:2307.09288, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.383217Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:254a2fef2af3990039059da48a6a728d7f29de17bf416db64b5dd16c40b59e80","observation_id":"9958ce9a-cad5-4d49-a379-5206e827f74d","resolution":{"observed_at":"2026-08-07T05:04:06.383217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.387398Z","title":"Image captioners are scalable vision learners too.Advances in Neural Information Processing Systems, 36:46830–46855, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.387398Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:fd5f4d2f560d5ef443632deaa4454210249f521026f68490404f1624f713d063","observation_id":"4d3844ff-2c30-4eac-be70-516b14819209","resolution":{"observed_at":"2026-08-07T05:04:06.387398Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.391287Z","title":"Visualizing data using t-sne.Journal of machine learning research, 9(11), 2008","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.391287Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:2c6264511abacf8636336a44700f7778da7ac9afdb51dbd9e55c726e6e84adfe","observation_id":"37d4ec21-92b9-4400-9990-4009e69ea965","resolution":{"observed_at":"2026-08-07T05:04:06.391287Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.10904","last_updated":"2022-05-15T23:20:46Z","snapshot_observed_at":"2026-08-06T05:59:00.316195Z","submitted_at":"2021-08-24T18:14:00Z","title":"SimVLM: Simple Visual Language Model Pretraining with Weak Supervision","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.10904","snapshot_observed_at":"2026-08-07T05:04:06.395146Z","title":"Simvlm: Simple visual language model pretraining with weak supervision.arXiv preprint arXiv:2108.10904, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.395146Z"},"links":{"cited_paper":"/paper/2108.10904","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d8af8e3b7d2c5d1688d9a8b92be0156d9ac2d4d19ec84d9819bf53aed52e1195","observation_id":"32f16b24-5e42-4983-ad77-b0bbfb6583fc","resolution":{"observed_at":"2026-08-07T05:04:06.395146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.244154Z","title":"Deepsqa: Understanding sensor data via question answering","venue":null,"work_id":"37b62882-8595-4af4-8304-cfbc54693275","year":2021},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.399583Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d77678c080d4997c5f0fe05a6c3043468fd89fd3830dca1aea63350ee671af8f","observation_id":"0f5fd389-71e8-4210-86ae-56438260f9d7","resolution":{"observed_at":"2026-08-07T05:04:07.248281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.232087Z","title":"Simper: Simple self-supervised learning of periodic targets","venue":null,"work_id":"d7cccd2f-f81a-421e-8047-4534a126ce6f","year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.403492Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:f9888983feaad1d5c1b276360ae1335d4994cd3998af6fc5e8e9b0f7352f6cb1","observation_id":"2fe0f453-ac9c-4e43-ac99-a0f6776a029e","resolution":{"observed_at":"2026-08-07T05:04:07.235854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.218234Z","title":"Artificial intelligence-enabled detection and assessment of parkinson’s disease using nocturnal breathing signals.Nature Medicine, 28(10):2207–2215, 2022","venue":null,"work_id":"6f972272-4a2f-45ad-bf4e-b54cc0c75110","year":2022},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.407556Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:cffebbe04d76904bae3c52bdfe9ba102ed5962cfdfd42e4f1e7921cb6955f385","observation_id":"6f4b7ac8-44a5-4c43-a168-7a8101efbcac","resolution":{"observed_at":"2026-08-07T05:04:07.222697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01917","last_updated":"2022-06-14T00:48:04Z","snapshot_observed_at":"2026-07-06T13:06:27.153765Z","submitted_at":"2022-05-04T07:01:14Z","title":"CoCa: Contrastive Captioners are Image-Text Foundation Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01917","snapshot_observed_at":"2026-08-07T05:04:06.411657Z","title":"Coca: Contrastivecaptionersareimage-textfoundationmodels","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.411657Z"},"links":{"cited_paper":"/paper/2205.01917","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:0b050f897e9198fe96cec51287c17e832bbff1ecbe6c9893536255839658c3dc","observation_id":"65d2b6bc-0f91-43a1-a9b2-5acffd1919a4","resolution":{"observed_at":"2026-08-07T05:04:06.411657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.02883","last_updated":"2025-07-18T23:00:52Z","snapshot_observed_at":"2026-08-09T21:40:17.050536Z","submitted_at":"2025-02-05T04:41:59Z","title":"SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.02883","snapshot_observed_at":"2026-08-07T05:04:06.416028Z","title":"Sensorchat: Answering qualitative and quantitative questions during long-term multimodal sensor interactions.arXiv preprint arXiv:2502.02883, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.416028Z"},"links":{"cited_paper":"/paper/2502.02883","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:b28c8e6c1b0455a982dd3597930de09c85a53c46dacc1fa1dc38d681b34c7231","observation_id":"540f3066-51d0-4383-985f-fac80ddfa244","resolution":{"observed_at":"2026-08-07T05:04:06.416028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:06.420069Z","title":"Self-supervised learning for human activity recognition using 700,000 person-days of wearable data.NPJ digital medicine, 7(1):91, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.420069Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d244a4dc07b781c8c27d8477b5c30e9fc93dd649a7751d068255d44938c383a7","observation_id":"2f528a76-0fae-48c7-9c0e-9d39ae8eb196","resolution":{"observed_at":"2026-08-07T05:04:06.420069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.196975Z","title":"Self-supervised contrastive pre-training for time series via time-frequency consistency.Advances in neural information processing systems, 35:3988–4003, 2022","venue":null,"work_id":"2d06d186-3b70-4237-91ae-e13be399ec0a","year":2022},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.424084Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:ba9afb1a315ccf2cbf1f5c593f6f537568438be8011884a0fe3451def2aac2be","observation_id":"64b80bf5-45a5-45ad-ab54-b25b0abadfba","resolution":{"observed_at":"2026-08-07T05:04:07.201104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.185215Z","title":"Unimts: Unified pre-training for motion time series.Advances in Neural Information Processing Systems, 37:107469–107493, 2024","venue":null,"work_id":"cde15807-878d-4c5b-b2da-c1fa3a7e5efd","year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.428103Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:05b9e488d459b44bc3a2628d7c0c15b7d026ecbac0e43fdaa756ae221eec425b","observation_id":"e17bfd02-cfd6-4e60-b257-9cf5ddeb4e45","resolution":{"observed_at":"2026-08-07T05:04:07.189177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.08849","last_updated":"2025-04-16T04:24:33Z","snapshot_observed_at":"2026-08-09T04:58:13.274938Z","submitted_at":"2024-08-16T17:20:45Z","title":"ECG-Chat: A Large ECG-Language Model for Cardiac Disease Diagnosis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.08849","snapshot_observed_at":"2026-08-07T05:04:06.432569Z","title":"Ecg-chat: A large ecg-language model for cardiac disease diagnosis.arXiv preprint arXiv:2408.08849, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.432569Z"},"links":{"cited_paper":"/paper/2408.08849","citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:2383e3b1052f13520ed99c7cb918664346272cdb6d6d8d7ef4cd3425a7c15f81","observation_id":"616e6eec-a80f-4473-98c8-546afe0cf388","resolution":{"observed_at":"2026-08-07T05:04:06.432569Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:04:07.173994Z","title":"Heart rate","venue":null,"work_id":"a2d8f258-1f69-4df4-b3b9-9d375bd852a9","year":2023},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.436794Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:bced56a60bd6bc3f71c05ee612f07197e74b281e8104f1da862956e6c03d11bd","observation_id":"015739ee-3db5-443a-bb3c-3a654a4d55db","resolution":{"observed_at":"2026-08-07T05:04:07.177450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.163017Z","title":null,"venue":null,"work_id":"ea8bc5d9-ecd4-4bb1-b172-e062e31250f2","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.441053Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:a6bd659590ef21355432838b20a40d766d6e99c38773103003aa8e672de352ed","observation_id":"2d9d619d-2e49-447f-a7aa-e544031645b2","resolution":{"observed_at":"2026-08-07T05:04:07.166381Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.151379Z","title":null,"venue":null,"work_id":"0e9a6f2e-12e5-4417-83b4-a090cd126737","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.445022Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:48c73319bc6dab6eb1ab774b21034ffd62b2baf7a41cf192e6fd71bb5323c4f5","observation_id":"c9faa8d7-a89a-488d-b622-bd613a967ad4","resolution":{"observed_at":"2026-08-07T05:04:07.155114Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.139668Z","title":null,"venue":null,"work_id":"3b609cba-4c94-4471-856d-5b7a9a993848","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.449269Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:2e0c5a37162de97f7926d3df48ae8e213448b19966e8ecd5c6eadb38e960d4ed","observation_id":"b1bd401d-23d2-4288-9286-167699fc650f","resolution":{"observed_at":"2026-08-07T05:04:07.143695Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.127919Z","title":null,"venue":null,"work_id":"1cd23982-37b9-4f7d-bd41-6ccd1d808857","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.453429Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:a5245a5f15c7f9ac3e0de01872edef0c9f511d47b83304346b28d54869c975c9","observation_id":"2570d5c2-a934-4a56-9155-d6f7ffdafa71","resolution":{"observed_at":"2026-08-07T05:04:07.131480Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.116001Z","title":null,"venue":null,"work_id":"5ab13696-0b86-48a7-91c9-77190001feb9","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.457475Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d42276d9f62a5957f0c7494826bc37f88ab19c3ec2c805196027ac4ca70c4eb1","observation_id":"525f199e-1e1a-4291-9819-353145113977","resolution":{"observed_at":"2026-08-07T05:04:07.119635Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.093487Z","title":null,"venue":null,"work_id":"febd1878-7916-4c3b-b85f-558e6241fe8e","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.466301Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d4d76d3fabf69dc18ca106afac245d3dfbb6814495d314c99256f0009afe1740","observation_id":"5cb75f77-6d89-4d2f-9fc7-2db97de16ebe","resolution":{"observed_at":"2026-08-07T05:04:07.097160Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.104629Z","title":null,"venue":null,"work_id":"9a1b48ab-26e7-4865-83b9-c0375d5c8bd9","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.470203Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:ffac293c3a2da4af13c046efd7c23295c7b5809f5693aaff1b9580e4491ac022","observation_id":"85c61af9-0577-4872-8d21-d41152512446","resolution":{"observed_at":"2026-08-07T05:04:07.108184Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.081905Z","title":null,"venue":null,"work_id":"07521dd1-76d5-4db1-8ef4-3a279c530ee5","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.474099Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:893a06b4c86c19cef70bf1fef38cc23857522f1a5c889848d82787fb47d4f9d4","observation_id":"37ad6251-b7cd-4482-8912-d006f054043b","resolution":{"observed_at":"2026-08-07T05:04:07.085395Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.071022Z","title":null,"venue":null,"work_id":"ade208ed-03e0-49f0-a323-6f657a057655","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.477949Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:34553eec5f12b2f9c6af31b3558f049ec70351b10fb1ae5328d3f6f6ef931284","observation_id":"00f0c55d-7c75-4f2b-bad9-b9ea82982f9c","resolution":{"observed_at":"2026-08-07T05:04:07.074569Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.059521Z","title":null,"venue":null,"work_id":"1aeb20d1-4801-475b-a840-507676811b09","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.481926Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:c477f7bfb3726d76e54d1014966a13655c30ad7a3a0b49317da537efa3c533d7","observation_id":"52eb4074-e543-4b2d-8bf9-9893bdf4629e","resolution":{"observed_at":"2026-08-07T05:04:07.063328Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.048557Z","title":null,"venue":null,"work_id":"28677a70-53de-44b0-b101-1bd7c31a09ae","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.486186Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:88aa6b83ea3f58c5bc6e9a9bca68adf50a9a62ffed5b5c4fac12d70ee6e90470","observation_id":"5c4654f6-459c-4415-bacf-749ea1246806","resolution":{"observed_at":"2026-08-07T05:04:07.051939Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.037498Z","title":null,"venue":null,"work_id":"f2a43fac-e4e5-474f-820b-b59e75bf4520","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.489947Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:4e12d1e1d2bcdb3b35bb1c7f9ed9ceaaaf9d34c4ec7e7818ce8e94568539bdbe","observation_id":"64b517df-c39c-47c0-b1b7-1e6842caca7f","resolution":{"observed_at":"2026-08-07T05:04:07.041017Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.025874Z","title":null,"venue":null,"work_id":"7ebe7bd7-c599-4e37-b35b-47f6a4c2c0d6","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.493808Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:e9e21b1ede77401075c2c450da03cb17b003e32f22484ec1c854ded02e1ab7d1","observation_id":"2d701e84-5be9-4ba3-96a8-416340c7e536","resolution":{"observed_at":"2026-08-07T05:04:07.029433Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.014250Z","title":null,"venue":null,"work_id":"00f0f42a-d76e-4e8f-97a3-43baef96f426","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.498691Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:28222b1594011e970f106643d448253506e7b41519d3726ebb8c0fab55134f69","observation_id":"010663d0-4049-4a75-80bf-6605051ed796","resolution":{"observed_at":"2026-08-07T05:04:07.017710Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:07.001008Z","title":null,"venue":null,"work_id":"f285d43b-369c-4718-b361-c4f59ce2f6f5","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.502662Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:41b3cab88d6121454795fc524517e5ee8bbc5c6df979d1086d91da5a759964c6","observation_id":"7391f12c-76ac-4333-8088-a50774059e52","resolution":{"observed_at":"2026-08-07T05:04:07.005380Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.986924Z","title":null,"venue":null,"work_id":"91d42510-39d2-4da5-b459-9c215c38404f","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.507046Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:00b986c0c5296583068152cd824547404bfb9b214a1e6d57f7de2339770a4fc1","observation_id":"c2041e5e-3c79-4e6f-8864-18f3ffb01339","resolution":{"observed_at":"2026-08-07T05:04:06.991855Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.971346Z","title":null,"venue":null,"work_id":"011bc50c-d126-4f92-ad73-cef43cf25bdd","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.511132Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:a7009434e7eb84f91acf2ef5a9294a4b57094d9215e0786e98774501a7ca96f5","observation_id":"67192f63-0889-4a36-8325-dfe2f6379ca3","resolution":{"observed_at":"2026-08-07T05:04:06.976279Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.957995Z","title":null,"venue":null,"work_id":"975592be-d93e-41f6-a162-2726b6839e8d","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.515210Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:4f1a57adf977414c7b121985b0c2c5b304e700d5fb89cbdc734a97eaa3cc1aad","observation_id":"b68b8483-a3a1-4882-8b93-09ce2ec4c8e0","resolution":{"observed_at":"2026-08-07T05:04:06.963260Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.941463Z","title":"Evaluate the feasibility of using the data provided by wrist-worn wearable devices to develop algorithms and scores to assess metabolic health","venue":null,"work_id":"0ff123be-1537-4621-956f-2ac613d7e0aa","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.519199Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:7fa827e0f10964e57265d1769cdb113086514eb28bfd84ae29529eca415279c6","observation_id":"b6152be0-404e-4f7e-9659-a9c1d9713313","resolution":{"observed_at":"2026-08-07T05:04:06.947549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.927593Z","title":null,"venue":null,"work_id":"3248d2de-a915-482c-bd6a-7dff710c8694","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.524099Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:2c238292a00de168f51c1d2299ae48538a509013c9acc206e153124ed5bcd75b","observation_id":"757b775f-c209-4e45-8f44-8003279c89f2","resolution":{"observed_at":"2026-08-07T05:04:06.931966Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.910295Z","title":null,"venue":null,"work_id":"32c648e1-32fe-491b-8277-f2f3b372459f","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.528368Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:0e8445eac4ffbf2bdf3adf7f90b5352d40039282521b85bcb93027d99d5f1a0b","observation_id":"ba2cc542-4db4-4ca6-9cd5-8a23ec48d6a5","resolution":{"observed_at":"2026-08-07T05:04:06.914996Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.896463Z","title":null,"venue":null,"work_id":"5975d0ad-f7f3-48d7-8d47-3057e64c629e","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.532984Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:738bbe601a4abc5f882e05e96447691542ec0698c2fa8cff0781a52bcf7bfdf3","observation_id":"6a4dadc4-b75c-43ba-9a74-4e76e3ebd14d","resolution":{"observed_at":"2026-08-07T05:04:06.900919Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.884738Z","title":null,"venue":null,"work_id":"73dfc3f9-a2d9-492c-b047-684667760771","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.537867Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:d0924ec3d26a819d6b9cf6bb70072a631943dd96aef723ec4a4550fdf0739092","observation_id":"0a331e88-89d6-456c-8054-499194c2848d","resolution":{"observed_at":"2026-08-07T05:04:06.888410Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.867705Z","title":"Activity by environmental context","venue":null,"work_id":"fdc81bb5-4bbc-4259-861a-f6d08165bcf4","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.541644Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:20d2ea7ce31bcc797da43f9e7a9179fa5561f2b46d7b21f170d6739f2501e3ba","observation_id":"2df69349-8ce1-42e0-9e2b-af284e688e7a","resolution":{"observed_at":"2026-08-07T05:04:06.873002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T05:04:06.852289Z","title":"Anxiety” and “Hypertension","venue":null,"work_id":"a6af6221-bb56-4fba-815a-b45a9e786f8f","year":null},"citing_paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors","version":1},"reference_index":730,"source":"pdf_text","source_observed_at":"2026-08-07T05:04:06.545949Z"},"links":{"citing_paper":"/paper/2506.09108"},"observation_digest":"sha256:065636c8a5cb63683499ad1511d3a299990a25795c55faa33951e87702990be1","observation_id":"8a7a5d57-7edf-40c6-ad01-01325ec2bd9c","resolution":{"observed_at":"2026-08-07T05:04:06.857490Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.09108","last_updated":"2025-06-10T17:13:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T20:05:30.020804Z","submitted_at":"2025-06-10T17:13:09Z","title":"SensorLM: Learning the Language of Wearable Sensors"},"reference_resolution":{"displayed":69,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":2,"unresolved":47,"verified_exact":0,"verified_fuzzy":19},"total_outbound_references":69},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 17 inbound Pith citation observations for arXiv:2506.09108."}