{"as_of":"2026-08-10T16:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7d6c191dac4cf3c0892aebb1dbcacbfbea787ad18d4503b7a6b8af86a27ee422","coverage":[{"denominator":180,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T04:32:43.263633Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.06430/citation-record","integrity":"/paper/2608.06430/integrity","json":"/paper/2608.06430/citation-record.json","paper":"/paper/2608.06430"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:42.793407Z","title":"AI for Critical Infrastructure Workshop@ IJCAI-24 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.793407Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:04ad94c602d1fa748fad03689e8af9f111f1f0ebe3d4848d09a8ae2e2426dea2","observation_id":"bb97a5d4-f999-4d6b-bb8d-a4e8b97348c1","resolution":{"observed_at":"2026-08-10T04:32:42.793407Z","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":"2026-08-10T04:32:42.799048Z","title":"Proceedings of the conference on health, inference, and learning , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.799048Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:bde013561d097b372aae7f4e7a84a4773d8da4366051b48f52468eecc0b73329","observation_id":"a173130b-4edc-4e68-927d-198900dff447","resolution":{"observed_at":"2026-08-10T04:32:42.799048Z","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":"2026-08-10T04:32:42.804113Z","title":"Neural Networks , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.804113Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:89c8a1950fc0aad34669ab0c8091b93cc813211e735cd1ed68f93d31c183bc65","observation_id":"b42e7b99-257d-49fb-8b6d-27b572f11f75","resolution":{"observed_at":"2026-08-10T04:32:42.804113Z","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":"2026-08-10T04:32:42.808931Z","title":"Proceedings of the AAAI conference on artificial intelligence , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.808931Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b268803f6f5f01c3114cd8ab4373217b8ca85eaa847f64c17da8ac72a1a1b9bb","observation_id":"12827dbb-e413-40f9-ba74-cb1ad8bee0db","resolution":{"observed_at":"2026-08-10T04:32:42.808931Z","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":"2026-08-10T04:32:42.813832Z","title":"Scientific Reports , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.813832Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:4fa1d9679609ea000cc73638967b1158a325d7613ce66dd66987ab21204854e1","observation_id":"a620cbc3-e212-4760-b3b7-4fbb7b8fc543","resolution":{"observed_at":"2026-08-10T04:32:42.813832Z","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":"2026-08-10T04:32:42.819000Z","title":"IEEE Journal of Biomedical and Health Informatics , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.819000Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:a5400ff216b60bc7dc140b559b2f731b3f5f5023b74e1b9c04a7060153d6b683","observation_id":"adbe9ebc-e364-463d-8a6d-aeac98411935","resolution":{"observed_at":"2026-08-10T04:32:42.819000Z","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":"2026-08-10T04:32:42.823939Z","title":"International Conference on Artificial Intelligence in Medicine , pages=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.823939Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d29815b5bacf30dd219bcfc25fc69941c11ecd4eca69ff5c5475c6ff92159a97","observation_id":"00bd51a7-b4f0-4863-8c8a-71a4bf82de43","resolution":{"observed_at":"2026-08-10T04:32:42.823939Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.09781","last_updated":"2025-02-13T21:30:21Z","snapshot_observed_at":"2026-08-10T12:19:20.309556Z","submitted_at":"2025-02-13T21:30:21Z","title":"Medical Applications of Graph Convolutional Networks Using Electronic Health Records: A Survey","version":1},"cited_work":{"arxiv_id":"2502.09781","doi":"10.48550/arxiv.2502.09781","metadata_source":"pith","pith_arxiv_id":"2502.09781","snapshot_observed_at":"2026-08-10T06:16:20.510975Z","title":"Medical Applications of Graph Convolutional Networks Using Electronic Health Records: A Survey","venue":"cs.LG","work_id":"078c2b85-cade-4017-accf-34d0152b970d","year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.829788Z"},"links":{"cited_paper":"/paper/2502.09781","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:8d78fb8568e0dd1fa3807a3ec38167496aa0e47ee3e91f4bc75839e4a8d8ef01","observation_id":"29099698-f433-4c12-959c-f877b2ba429d","resolution":{"observed_at":"2026-08-10T04:32:44.098263Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":"10.48550/arxiv.2511.01249","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"doi:10.48550/arXiv.2511.01249 , urldate =","venue":"ArXiv.org","work_id":"7b885507-461b-410a-9026-b3442788a290","year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.835029Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d378d4078fa34802c2a68bf49870772a152207c59b76c0adf6b8d579e8c7dd73","observation_id":"9500c067-f5a7-480e-90a9-5ecb5a8856b8","resolution":{"observed_at":"2026-08-10T04:32:44.075225Z","resolver_source":"doi","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:42.840507Z","title":"NeurIPS 2025 Workshop on Learning from Time Series for Health , year =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.840507Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:f8ddf93dd971e448fe0f8e472bf76987a4ce468c9d23c8d8d3272df35b930ed8","observation_id":"8145a916-d308-4cb0-ac92-b391c94ae5a4","resolution":{"observed_at":"2026-08-10T04:32:42.840507Z","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":"2026-08-10T04:32:42.845397Z","title":"bioRxiv , pages=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.845397Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:45962429ff0ce31372cc3679647b187449b79d10ba7c209a2f0cee9e6cc24d2e","observation_id":"2a2f1f69-a9f9-4278-8380-146eadfb7517","resolution":{"observed_at":"2026-08-10T04:32:42.845397Z","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":"2026-08-10T04:32:42.850169Z","title":"Temporal Graph Learning Workshop@ KDD 2025 , year=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.850169Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b5e485fcbc534795f04917ce876a7a0395634d8a0d5ae311b6ad0415b3ad0420","observation_id":"919a77f3-df86-4754-979a-115cfd1b5c0d","resolution":{"observed_at":"2026-08-10T04:32:42.850169Z","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":"2026-08-10T04:32:42.854976Z","title":"IJCAI: proceedings of the conference , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.854976Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:13f91ecf46b686cf89df5ca965ed984bf4c6a1a57b649a869c4724c066d3d620","observation_id":"c27cec5a-d5ea-44ca-90da-d6c82215d4d4","resolution":{"observed_at":"2026-08-10T04:32:42.854976Z","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":"2026-08-10T04:32:42.859236Z","title":"International Journal of Medical Informatics , pages=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.859236Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:6f9331dbf18a43cbe964852df482d575606f87395c3e253951dccdd6a9252948","observation_id":"d46666ad-15cd-42f1-823f-7fa05ef862fa","resolution":{"observed_at":"2026-08-10T04:32:42.859236Z","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":"2026-08-10T04:32:42.863687Z","title":"Journal of biomedical informatics , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.863687Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:5407a0b9a219a4ec04bad6574948b4f8b3799e2d90026cf6f9adc59e5bdea506","observation_id":"c99c36b0-6df3-465c-a0cf-b13cf0b2a011","resolution":{"observed_at":"2026-08-10T04:32:42.863687Z","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":"2026-08-10T04:32:42.868442Z","title":"Journal of Discrete Mathematical Sciences and Cryptography , volume=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.868442Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:364ac8c9489170a5d8a7f127934d4cbd8a8469ff6d59e8ae20f46acd187a590f","observation_id":"93540ca4-6fe4-49d7-aca4-49e9b5129dac","resolution":{"observed_at":"2026-08-10T04:32:42.868442Z","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":"2026-08-10T04:32:42.873548Z","title":"IEEE Journal of Biomedical and Health Informatics , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.873548Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d891553955b2f97f995e2e61e1138dadcce7db987ce4ffddab8ee7f5f0cedb98","observation_id":"983cc7f5-d649-4441-9f8e-84afd5c44236","resolution":{"observed_at":"2026-08-10T04:32:42.873548Z","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":"2026-08-10T04:32:42.878762Z","title":"NPJ digital medicine , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.878762Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:94605791be86bab57882a5d41874a7f05bed4aeb04849c8033485f27daba292d","observation_id":"4967c6b2-5d06-40ba-a9a2-9779650bfe27","resolution":{"observed_at":"2026-08-10T04:32:42.878762Z","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":"2026-08-10T04:32:42.883811Z","title":"2025 , school=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.883811Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:efff564b3feaedb3d65982891544d2fbb3f8fec496de29ab1cd4a8ff529d0663","observation_id":"5948ddac-7346-49c2-92e5-a0abb089c875","resolution":{"observed_at":"2026-08-10T04:32:42.883811Z","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":"2026-08-10T04:32:42.888753Z","title":"IEEE Transactions on Big Data , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.888753Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:db88c4170d31947bd2582c1cd94bc603d56800ea7796db644850defa55f789d4","observation_id":"1225b795-c608-4de8-beb5-815bb2ae3c8c","resolution":{"observed_at":"2026-08-10T04:32:42.888753Z","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":"2026-08-10T04:32:42.893603Z","title":"Journal of Biomedical Informatics , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.893603Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:40b7b89c4150959ec5246fd72b16d1c1a52d4bd55eaf56b48f39ddaf9448b7d8","observation_id":"544b61b8-9274-4665-9f8c-0a387df555ac","resolution":{"observed_at":"2026-08-10T04:32:42.893603Z","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":"2026-08-10T04:32:42.898228Z","title":"Information Processing & Management , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.898228Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d262289008c1ed8fbc784f63dbb8421a08997305853a1c31a09b53e06694f491","observation_id":"b7cfcd0e-0308-4c5b-ac53-a6c76b2010c9","resolution":{"observed_at":"2026-08-10T04:32:42.898228Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.14552","last_updated":"2024-06-12T17:44:44Z","snapshot_observed_at":"2026-07-06T16:36:55.519052Z","submitted_at":"2023-10-23T04:15:39Z","title":"Knowledge-Induced Medicine Prescribing Network for Medication Recommendation","version":2},"cited_work":{"arxiv_id":"2310.14552","doi":"10.48550/arxiv.2310.14552","metadata_source":"pith","pith_arxiv_id":"2310.14552","snapshot_observed_at":"2026-08-10T06:16:20.510975Z","title":"Knowledge-Induced Medicine Prescribing Network for Medication Recommendation","venue":"cs.LG","work_id":"583a51e6-83e2-4b83-8c26-41c3002fd600","year":2023},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.902875Z"},"links":{"cited_paper":"/paper/2310.14552","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:54bc5101f93acedb5127dd4c4afdf91fb473e21a36296f6ca4b48faf229e649d","observation_id":"b99441c7-f608-4578-8b27-58dba0d1419c","resolution":{"observed_at":"2026-08-10T04:32:43.990922Z","resolver_source":"local_arxiv","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":"2211.10542","last_updated":"2025-07-22T14:32:56Z","snapshot_observed_at":"2026-08-10T00:34:57.403445Z","submitted_at":"2022-11-19T00:04:57Z","title":"Hodge-Decomposition of Functional Brain Networks","version":4},"cited_work":{"arxiv_id":"2211.10542","doi":"10.48550/arxiv.2211.10542","metadata_source":"pith","pith_arxiv_id":"2211.10542","snapshot_observed_at":"2026-08-10T06:16:20.510975Z","title":"Hodge-Decomposition of Functional Brain Networks","venue":"q-bio.NC","work_id":"21a6fb17-4013-4068-884e-82da306d3aa6","year":2022},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.908973Z"},"links":{"cited_paper":"/paper/2211.10542","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:82ac4596a57eaf5bcdd14a13711aeea3988151ffbd4cf4be1892348d39cae216","observation_id":"a1589bb6-6a5d-42f1-9c94-1ed11345cdad","resolution":{"observed_at":"2026-08-10T04:32:43.968526Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:42.914153Z","title":"IEEE Transactions on Pattern Analysis and Machine Intelligence , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.914153Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d6fd2b3281c391718c562b4a2416a0b38498948d9ddff70b88375785e00aeea3","observation_id":"ef419a66-8900-4c1c-8de9-02ca33f94abc","resolution":{"observed_at":"2026-08-10T04:32:42.914153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.17312","last_updated":"2025-06-18T10:36:11Z","snapshot_observed_at":"2026-08-03T18:02:47.846945Z","submitted_at":"2025-06-18T10:36:11Z","title":"Heterogeneous Temporal Hypergraph Neural Network","version":1},"cited_work":{"arxiv_id":"2506.17312","doi":"10.48550/arxiv.2506.17312","metadata_source":"pith","pith_arxiv_id":"2506.17312","snapshot_observed_at":"2026-08-10T06:16:20.510975Z","title":"Heterogeneous Temporal Hypergraph Neural Network","venue":"cs.SI","work_id":"0d8c7788-bc0b-40ca-b1a7-e20ad46199c0","year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.918930Z"},"links":{"cited_paper":"/paper/2506.17312","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:98944849fb66d18c576d3e82a2d428aa52a17c9148080817b78243cb060d28d3","observation_id":"6b135bb7-baca-4d69-8311-7226e7462a04","resolution":{"observed_at":"2026-08-10T04:32:43.946706Z","resolver_source":"local_arxiv","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":"2010.10728","last_updated":"2021-01-18T08:53:28Z","snapshot_observed_at":"2026-07-06T10:06:28.380264Z","submitted_at":"2020-10-21T02:49:22Z","title":"Heterogeneous Hypergraph Embedding for Graph Classification","version":3},"cited_work":{"arxiv_id":"2010.10728","doi":"10.48550/arxiv.2010.10728","metadata_source":"pith","pith_arxiv_id":"2010.10728","snapshot_observed_at":"2026-08-10T06:16:20.510975Z","title":"Heterogeneous Hypergraph Embedding for Graph Classification","venue":"cs.SI","work_id":"1ab80860-8bf9-46c3-ba1d-05e3f9c01385","year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.924575Z"},"links":{"cited_paper":"/paper/2010.10728","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:c74b0d2966d60989f2a3d76a027187abdfb5dbcb2b69a3f8f27122ebd94d5b05","observation_id":"ef7dfef3-d2fe-49d9-a3af-ed1dd2003d62","resolution":{"observed_at":"2026-08-10T04:32:43.921515Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:42.929659Z","title":"International Semantic Web Conference , pages=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.929659Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:a7476260764cec932a32a151b0a7f0eb935b7a559b7fab6a65fcb6968fc58052","observation_id":"1c52b03a-1925-43f9-9323-f4bf5c90d515","resolution":{"observed_at":"2026-08-10T04:32:42.929659Z","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":"2026-08-10T04:32:42.934279Z","title":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.934279Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:9aa89a7c7eadf7987a500420b8bf101e33f13e353095323901d883f0a4560fa7","observation_id":"940314ec-8928-4ee0-9165-6e4e5c2288b8","resolution":{"observed_at":"2026-08-10T04:32:42.934279Z","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":"10.48550/arxiv.2603.18459","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"doi:10.48550/arXiv.2603.18459 , urldate =","venue":"arXiv (Cornell University)","work_id":"26374f3f-7293-4503-9212-381b380edf47","year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.938978Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:7a92063d6011fb883d67f95b2cd2a2d45fb61891995f85a48c6f4ee8f45ac210","observation_id":"ef212d28-34f9-4ef1-bc47-b88311e0c706","resolution":{"observed_at":"2026-08-10T04:32:43.897898Z","resolver_source":"doi","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":"2003.01332","last_updated":"2020-03-03T04:49:21Z","snapshot_observed_at":"2026-08-09T00:12:39.478411Z","submitted_at":"2020-03-03T04:49:21Z","title":"Heterogeneous Graph Transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.01332","snapshot_observed_at":"2026-08-10T04:32:42.943655Z","title":"Heterogeneous","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.943655Z"},"links":{"cited_paper":"/paper/2003.01332","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:3d5f8716b922174b034464f3238eabbde2f3619e1f49d4ce6fa7849d3d9c284d","observation_id":"27e66291-b65b-4d8a-9039-36cc30418ec8","resolution":{"observed_at":"2026-08-10T04:32:42.943655Z","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":"2026-08-10T04:32:42.949409Z","title":"AMIA Summits on Translational Science Proceedings , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.949409Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b5519a6b1176309dd3eaa99da9389f144a672ca134d2d7fd2412a81a152daec3","observation_id":"2b85e8fd-102e-4629-ac79-cedf39558d90","resolution":{"observed_at":"2026-08-10T04:32:42.949409Z","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":"2026-08-10T04:32:42.953920Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.953920Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:f424f028f6072cc7115098572ae9489f8b5df9e24c620e2febfea0500373c778","observation_id":"e03791cc-99e1-4019-af8f-8ade5d93fb5d","resolution":{"observed_at":"2026-08-10T04:32:42.953920Z","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":"2026-08-10T04:32:42.958686Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.958686Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:85130e29cc6edc06f1469b5c88aec794936bfd4bf535398418ec9f4385fb66c6","observation_id":"6dcc5e90-e573-4776-9932-0db293c67e96","resolution":{"observed_at":"2026-08-10T04:32:42.958686Z","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":"2026-08-10T04:32:42.963390Z","title":"IEEE Access , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.963390Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:2021466289827a84a9f25030ec9a266a95a53a2b0f60b0a74ed5502ce22960f0","observation_id":"31188a47-6599-4e63-bab7-6d0cf0655025","resolution":{"observed_at":"2026-08-10T04:32:42.963390Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.03940","last_updated":"2021-01-11T15:04:07Z","snapshot_observed_at":"2026-07-06T10:31:30.836845Z","submitted_at":"2021-01-11T15:04:07Z","title":"Predicting Patient Outcomes with Graph Representation Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.03940","snapshot_observed_at":"2026-08-10T04:32:42.968108Z","title":"Predicting","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.968108Z"},"links":{"cited_paper":"/paper/2101.03940","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:113493b452e68f93c975795bd6f33c106cb88f287b59cb5ffdface518fc20883","observation_id":"d5ff1665-ba4c-4263-b143-f339a5d97ad9","resolution":{"observed_at":"2026-08-10T04:32:42.968108Z","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":"2026-08-10T04:32:42.972974Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.972974Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:49c074a67bd86eb8b134f2516fefec0365514089f12103eb1ce971ae645037ad","observation_id":"d6c9f258-d2d9-4f81-b1d0-ff8bbe71b01f","resolution":{"observed_at":"2026-08-10T04:32:42.972974Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.11368","last_updated":"2023-11-19T16:34:56Z","snapshot_observed_at":"2026-08-09T23:21:27.708804Z","submitted_at":"2023-11-19T16:34:56Z","title":"Self-Supervised Pretraining for Heterogeneous Hypergraph Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.11368","snapshot_observed_at":"2026-08-10T04:32:42.977273Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.977273Z"},"links":{"cited_paper":"/paper/2311.11368","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:fde1930bb8f4f6637c1457d6f921bfda3ffee168d562118d8a782794a25f0cdc","observation_id":"bf63e455-cd89-466e-8436-cbeda2bfe793","resolution":{"observed_at":"2026-08-10T04:32:42.977273Z","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":"10.48550/arxiv.2308.12029","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"and Kwok, James T","venue":"arXiv (Cornell University)","work_id":"a858df25-a88f-4183-8ac6-e96e4641b8d7","year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.982403Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:034460e899226aab801de0e3c1ac6d76f7ddc60f0c51bdf5dbee2daa63d12a4f","observation_id":"dec9ce8d-235b-4235-9c02-94a6a5f851f5","resolution":{"observed_at":"2026-08-10T04:32:43.772575Z","resolver_source":"doi","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":"1710.10903","last_updated":"2018-02-04T19:13:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-10-30T12:41:12Z","title":"Graph Attention Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10903","snapshot_observed_at":"2026-08-10T04:32:42.986970Z","title":"arXiv preprint arXiv:1710.10903 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.986970Z"},"links":{"cited_paper":"/paper/1710.10903","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:18471288a90b55063ebea964701d913157aae114ade72dff8fad46bbe4dc621d","observation_id":"dd46bb41-6ab2-4d6e-a61c-6652a907566b","resolution":{"observed_at":"2026-08-10T04:32:42.986970Z","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":"2026-08-10T04:32:42.991544Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.991544Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:35bac45c4ec4355755861936f931404c63f1296c56813b56df5e49c60d91fdb9","observation_id":"61720294-7eb0-4989-97b8-a94a76f730e3","resolution":{"observed_at":"2026-08-10T04:32:42.991544Z","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":"2026-08-10T04:32:42.996009Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:42.996009Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:73ab0b5725fb814407c59496d9ae2115bb6384a5dff44411e5b664fda64b4728","observation_id":"ef58f246-a826-4781-8667-18667c38d4df","resolution":{"observed_at":"2026-08-10T04:32:42.996009Z","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":"2026-08-10T04:32:43.000584Z","title":"Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.000584Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:bf1c9a390748ec6c56bf6f74f68a3b43f056719a2daebf834d5a213b41a97d50","observation_id":"d836f77f-0aca-4e33-a14c-70e21baa4612","resolution":{"observed_at":"2026-08-10T04:32:43.000584Z","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":"2026-08-10T04:32:43.005063Z","title":"2022 IEEE International Conference on Knowledge Graph (ICKG) , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.005063Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b24bd7f3022d5d1cf9a74481c5958ce891d2f41f3f56fd877e79b18317c066bc","observation_id":"8ea145c7-a686-4423-bf17-5506a4312aec","resolution":{"observed_at":"2026-08-10T04:32:43.005063Z","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":"2026-08-10T04:32:43.009376Z","title":"Data Intelligence , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.009376Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:4bffad94bd68ffa6bd63115bfca756d74c7fcbb4dc9b849215c7773256342e7e","observation_id":"a22b7923-a9ad-4889-9a4e-12d1ec825cc3","resolution":{"observed_at":"2026-08-10T04:32:43.009376Z","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":"2026-08-10T04:32:43.013713Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.013713Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:4a8415236b0211da3944dc7244e2357fb5475769e09ff394a336010fd1f1c6aa","observation_id":"f34d6351-caf0-4b1b-8c61-624deb5323d1","resolution":{"observed_at":"2026-08-10T04:32:43.013713Z","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":"2026-08-10T04:32:43.018024Z","title":"Proceedings of the 2018 World Wide Web Conference , pages=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.018024Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:3568decb2a589573cd925302200e77846d4dc73087e6d77376f2852a54d76617","observation_id":"9a3867cc-9ff0-4d3e-9c92-4a77b1fa24e6","resolution":{"observed_at":"2026-08-10T04:32:43.018024Z","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":"2026-08-10T04:32:43.022939Z","title":"IEEE transactions on neural networks , volume=","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.022939Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:7e70898eda5756de5088a0ed68a6e404d021c25ba93e124e46d07364f49203c0","observation_id":"376bb8cc-c789-423b-9482-d79f5f8313b7","resolution":{"observed_at":"2026-08-10T04:32:43.022939Z","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":"2026-08-10T04:32:43.027423Z","title":"Proceedings","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.027423Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:1da0bce665b8373594156999cc29c4a55c8b0b969a846a3c063c75cc3ff0a4c6","observation_id":"aa4041a3-56d3-4e60-9369-21ce44533950","resolution":{"observed_at":"2026-08-10T04:32:43.027423Z","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":"2026-08-10T04:32:43.031922Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.031922Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:776ffb948a838300a9b4076cee5beb0e12a0d74f1f86c1aa323d6c80448b44e9","observation_id":"25555c84-10b9-4a92-9b3a-d8ed5dfe7962","resolution":{"observed_at":"2026-08-10T04:32:43.031922Z","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":"2026-08-10T04:32:43.036155Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.036155Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:2cce29f2cdde745fedd4f19cd8c668787ac900963ed1b5c5901350678f6a29ef","observation_id":"7a9d7820-8eae-4207-a324-221a6081821d","resolution":{"observed_at":"2026-08-10T04:32:43.036155Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.05493","last_updated":"2017-09-22T21:36:00Z","snapshot_observed_at":"2026-07-06T04:36:48.493556Z","submitted_at":"2015-11-17T18:10:12Z","title":"Gated Graph Sequence Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.05493","snapshot_observed_at":"2026-08-10T04:32:43.040624Z","title":"arXiv preprint arXiv:1511.05493 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.040624Z"},"links":{"cited_paper":"/paper/1511.05493","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d774795226a83b903e0340f45df18f0fcd2378989afe9973bd7cff92775643c0","observation_id":"16b25b5c-4cb2-4457-9d4c-34ea5588b517","resolution":{"observed_at":"2026-08-10T04:32:43.040624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.11198","last_updated":"2020-11-03T19:20:22Z","snapshot_observed_at":"2026-07-06T09:14:40.956312Z","submitted_at":"2020-04-23T14:46:10Z","title":"SIGN: Scalable Inception Graph Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.11198","snapshot_observed_at":"2026-08-10T04:32:43.045589Z","title":"arXiv preprint arXiv:2004.11198 , year=","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.045589Z"},"links":{"cited_paper":"/paper/2004.11198","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:251702dcefc8fd9040c6f8f894d28b23ad08474f7c256aa39d60dd8e3f6cee4f","observation_id":"4f5b8c64-ec33-4635-81d1-9a4f53fa8195","resolution":{"observed_at":"2026-08-10T04:32:43.045589Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.09376","last_updated":"2021-07-01T10:08:16Z","snapshot_observed_at":"2026-08-07T01:23:40.296899Z","submitted_at":"2021-04-19T15:08:06Z","title":"Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.09376","snapshot_observed_at":"2026-08-10T04:32:43.050474Z","title":"arXiv preprint arXiv:2104.09376 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.050474Z"},"links":{"cited_paper":"/paper/2104.09376","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:219004a00b8dda5f24be2a617b9ff9bddd443ffca131dc19aa3a5d6732fb3743","observation_id":"d8699ecd-2fbd-4a71-a9f1-9aac16e75d4a","resolution":{"observed_at":"2026-08-10T04:32:43.050474Z","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":"2026-08-10T04:32:43.055438Z","title":"AI Open , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.055438Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b55939714b7b1854ee2b6b02606e979764a9cd387e9ebd6fa2a85aaed0c2bbfd","observation_id":"de068a84-309d-4b94-a5f5-91475f3b705e","resolution":{"observed_at":"2026-08-10T04:32:43.055438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.14867","last_updated":"2020-11-30T15:03:47Z","snapshot_observed_at":"2026-07-06T10:19:02.419450Z","submitted_at":"2020-11-30T15:03:47Z","title":"A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources","version":1},"cited_work":{"arxiv_id":"2011.14867","doi":null,"metadata_source":"pith","pith_arxiv_id":"2011.14867","snapshot_observed_at":"2026-08-10T04:32:44.489210Z","title":"A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources","venue":"cs.SI","work_id":"596eb3e0-8350-4dbc-8395-df3d151210ca","year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.060291Z"},"links":{"cited_paper":"/paper/2011.14867","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:2593481653908ae67ed6b43e9670fbeb337f32b999426bfa135b010ea1a73c57","observation_id":"61d8c253-9364-42b7-bc16-d81e21fbb819","resolution":{"observed_at":"2026-08-10T04:32:44.494823Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:43.065093Z","title":"IEEE Transactions on Neural Networks and Learning Systems , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.065093Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:cb9b67cde015e79a19b8c57692862414f7ba23215e324a1c68bbc8b8935e5dd4","observation_id":"cd3a67ef-eaff-4885-bf74-f98d431da197","resolution":{"observed_at":"2026-08-10T04:32:43.065093Z","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":"2026-08-10T04:32:43.069877Z","title":"Hamilton and Rex Ying and Jure Leskovec , title =","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.069877Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:79eb3c55ffb3288d850ddffe1866d447850f13f608536c93562d578e6c97d7fa","observation_id":"0bf480ea-b3ca-4977-8cbb-f4777703db10","resolution":{"observed_at":"2026-08-10T04:32:43.069877Z","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":"2026-08-10T04:32:43.074651Z","title":"GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs , journal =","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.074651Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d0d4e6052f71e2224b6c0d0e59eb003934829b1677081992a6933982d7779aad","observation_id":"390f5bfc-b2cb-4f9d-81ef-2484a792c62f","resolution":{"observed_at":"2026-08-10T04:32:43.074651Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.14722","last_updated":"2020-12-29T12:12:37Z","snapshot_observed_at":"2026-07-06T10:28:28.378332Z","submitted_at":"2020-12-29T12:12:37Z","title":"Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learning","version":1},"cited_work":{"arxiv_id":"2012.14722","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.14722","snapshot_observed_at":"2026-08-10T04:32:44.467034Z","title":"Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learning","venue":"cs.LG","work_id":"e51c040e-741c-470e-a46d-13281ba0cb0a","year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.079331Z"},"links":{"cited_paper":"/paper/2012.14722","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:031afd8a883a31f99a170f0a3250eec0b08d89ebc64906e115f67ebf91a8b957","observation_id":"5bf402d1-3bec-439a-8946-0bdd23dd5deb","resolution":{"observed_at":"2026-08-10T04:32:44.472517Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:43.084198Z","title":"The World Wide Web Conference , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.084198Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:ca2079654b9fcbfb903d3fe34d2f65c66edcfdb5ca516b047a00c71fd038a031","observation_id":"88d1c500-f9c8-4078-b3a9-c1a820b318cd","resolution":{"observed_at":"2026-08-10T04:32:43.084198Z","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":"2026-08-10T04:32:43.089495Z","title":"Proceedings of The Web Conference 2020 , pages=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.089495Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:e414233378587549ce70ab3e9b2543ea15d826052bc8cd3e14c713baeca93de1","observation_id":"229e5465-8370-4bf9-8e36-3af1f9c68ebd","resolution":{"observed_at":"2026-08-10T04:32:43.089495Z","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":"2026-08-10T04:32:43.094701Z","title":"European semantic web conference , pages=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.094701Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:23a3f6096bcdf88caefc93fb89a584af4606638005842715dee50d05d816a80e","observation_id":"a5fb1287-d604-461b-ad85-226fa7c8c8db","resolution":{"observed_at":"2026-08-10T04:32:43.094701Z","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":"2026-08-10T04:32:43.099911Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.099911Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:eb58ae6628e97b2ba2a062f15045916a2c70d9b65ba1ceb26c37b5806b472264","observation_id":"f918baef-272c-45bd-872f-cdccf57a32bd","resolution":{"observed_at":"2026-08-10T04:32:43.099911Z","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":"2026-08-10T04:32:43.104442Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.104442Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:69b00569eacde25f94f70847a2e0144ca69370d28c26c9d90dbf09df10041c99","observation_id":"f10c2fa5-4967-435f-981c-c2523e57536c","resolution":{"observed_at":"2026-08-10T04:32:43.104442Z","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":"2026-08-10T04:32:43.108924Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.108924Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:8647ef4b840f0dc466ebd81f2f3be81e6e0e72546fe910f8fe5cbcf23f71f4da","observation_id":"1ae3223e-4201-4542-b8cc-72dc21c5c5c0","resolution":{"observed_at":"2026-08-10T04:32:43.108924Z","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":"2026-08-10T04:32:43.113433Z","title":"Multi-relational poincar","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.113433Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:cbca20c553c0f25b3d2f0d280835bdf23f6a65e2fc9acbd10be58bc56c0d50da","observation_id":"91181bbc-6b01-432a-b180-e73e7f8ffd8d","resolution":{"observed_at":"2026-08-10T04:32:43.113433Z","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":"2026-08-10T04:32:43.117854Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.117854Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:c0be3d8b0f5fc417867536f15244eeffcc7169343827b18a5a756525881210fc","observation_id":"52e73ea9-7588-458f-a29a-9f7ac980ed95","resolution":{"observed_at":"2026-08-10T04:32:43.117854Z","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":"2026-08-10T04:32:43.121858Z","title":"Proceedings of the IEEE , volume=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.121858Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:6a35126adf6afd6308ddbc8b01cf726dc499708f0ca8670cc2b3a6614bfcc768","observation_id":"7aeeb706-c2c1-4e78-9566-eb24372e1fbf","resolution":{"observed_at":"2026-08-10T04:32:43.121858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6575","last_updated":"2015-08-29T15:08:45Z","snapshot_observed_at":"2026-08-10T09:43:27.820941Z","submitted_at":"2014-12-20T01:37:16Z","title":"Embedding Entities and Relations for Learning and Inference in Knowledge Bases","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6575","snapshot_observed_at":"2026-08-10T04:32:43.126234Z","title":"arXiv preprint arXiv:1412.6575 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.126234Z"},"links":{"cited_paper":"/paper/1412.6575","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:70768f346b16cb5803ea99453a5035e0411573567c0f4b7dd279679b52d8fa9c","observation_id":"1da72cf3-c2d6-4728-97fc-41de8514d94e","resolution":{"observed_at":"2026-08-10T04:32:43.126234Z","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":"2026-08-10T04:32:43.131222Z","title":"Twenty-ninth AAAI conference on artificial intelligence , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.131222Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:c14b7ea46e53d071bbc81462961a7355a8d3afaf35444276683da2fc9dd7c09d","observation_id":"024e08e9-a807-4d77-a67b-9891f2d1cf85","resolution":{"observed_at":"2026-08-10T04:32:43.131222Z","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":"2026-08-10T04:32:43.136062Z","title":"HerGePred: Heterogeneous Network Embedding Representation for Disease Gene Prediction , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.136062Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:8ea14e2df4416ce3d4d8fa084b6399e3e309a2f64244f612fde296d2f0d59989","observation_id":"284cdbf8-2e8c-4194-bc29-6ca4f4131594","resolution":{"observed_at":"2026-08-10T04:32:43.136062Z","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":"2026-08-10T04:32:43.140243Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.140243Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d4a275ee8c10085bddbff5aa09fd00251e00239d4852451637f5040570e43f18","observation_id":"6e07823b-0341-44f1-b551-47e5f57b65c0","resolution":{"observed_at":"2026-08-10T04:32:43.140243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.00687","last_updated":"2021-02-25T02:06:27Z","snapshot_observed_at":"2026-08-09T05:17:43.055948Z","submitted_at":"2020-05-02T03:09:50Z","title":"Open Graph Benchmark: Datasets for Machine Learning on Graphs","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.00687","snapshot_observed_at":"2026-08-10T04:32:43.144169Z","title":"arXiv preprint arXiv:2005.00687 , year=","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.144169Z"},"links":{"cited_paper":"/paper/2005.00687","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:fb9b06958abd9bd8edbb9c623c0a50cc8fac6c4e3f705bb1902acffd9b244f66","observation_id":"e50552a8-7fb1-4d63-8e36-34d76fe9582e","resolution":{"observed_at":"2026-08-10T04:32:43.144169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.08663","last_updated":"2020-07-16T21:46:33Z","snapshot_observed_at":"2026-08-06T13:06:20.395369Z","submitted_at":"2020-07-16T21:46:33Z","title":"TUDataset: A collection of benchmark datasets for learning with graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.08663","snapshot_observed_at":"2026-08-10T04:32:43.148873Z","title":"arXiv preprint arXiv:2007.08663 , year=","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.148873Z"},"links":{"cited_paper":"/paper/2007.08663","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:073f6ec60a42e05827e3c08e07af99c60681127542607ab7558d4da7413ce0df","observation_id":"96c195a8-9ad5-4fae-9ace-964f17ffa249","resolution":{"observed_at":"2026-08-10T04:32:43.148873Z","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":"2026-08-10T04:32:43.153645Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.153645Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:10007bb7c2885336c472759ee35e4d1e2378dd612aba6f9f55b2c3dc6701b730","observation_id":"f962c897-2865-4485-b618-c63d11259fd9","resolution":{"observed_at":"2026-08-10T04:32:43.153645Z","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":"2026-08-10T04:32:43.157987Z","title":", author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.157987Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b9f72d288b9b3bc29b42d16c1700c3c1002b32586e75b54221812448f390ad21","observation_id":"6afdd40d-ff00-4971-9f9a-28ed252b05b0","resolution":{"observed_at":"2026-08-10T04:32:43.157987Z","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":"2026-08-10T04:32:43.162436Z","title":"ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) , volume=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.162436Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:ffb272b9b0154f5cbb8beefa5c9d741361b8dc4056a3885688c5b1f51632dd4f","observation_id":"6fa0f192-5e3c-4a21-9b28-fe1cc6fa2636","resolution":{"observed_at":"2026-08-10T04:32:43.162436Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.05688","last_updated":"2022-09-25T05:14:30Z","snapshot_observed_at":"2026-08-09T17:42:09.035325Z","submitted_at":"2020-12-10T14:16:46Z","title":"GDA-HIN: A Generalized Domain Adaptive Model across Heterogeneous Information Networks","version":3},"cited_work":{"arxiv_id":"2012.05688","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.05688","snapshot_observed_at":"2026-08-10T04:32:44.394831Z","title":"GDA-HIN: A Generalized Domain Adaptive Model across Heterogeneous Information Networks","venue":"cs.LG","work_id":"97fd494b-1c23-491a-8cc8-ad9afcfca4c9","year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.166871Z"},"links":{"cited_paper":"/paper/2012.05688","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:838ad277dc3f6e1512afa486ce0450d743bcd972e2d4de8aca4f7fae34276532","observation_id":"514a4bd9-793b-45c7-9395-4b87b66c10f4","resolution":{"observed_at":"2026-08-10T04:32:44.401140Z","resolver_source":"local_arxiv","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":"1906.00684","last_updated":"2019-08-19T23:34:19Z","snapshot_observed_at":"2026-08-10T12:18:42.681501Z","submitted_at":"2019-06-03T10:11:15Z","title":"DANE: Domain Adaptive Network Embedding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.00684","snapshot_observed_at":"2026-08-10T04:32:43.171960Z","title":"arXiv preprint arXiv:1906.00684 , year=","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.171960Z"},"links":{"cited_paper":"/paper/1906.00684","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:014be79dfa898373a82bcb8a54e02ce50d05ecc2268a71df432e763f54b8b4ad","observation_id":"efece6eb-f32b-4349-9eea-afa91c3fc0d8","resolution":{"observed_at":"2026-08-10T04:32:43.171960Z","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":"2026-08-10T04:32:43.176927Z","title":"Proceedings of the IEEE conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.176927Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:79401737bbe23571f1e4fa1164bbd955c63436f0de9e675b0427955067b038c0","observation_id":"e16887f4-697f-4cdb-8b79-23bff86def42","resolution":{"observed_at":"2026-08-10T04:32:43.176927Z","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":"2026-08-10T04:32:43.181500Z","title":"Proceedings of the European Conference on Computer Vision (ECCV) , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.181500Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b686a7787302bebe81c4cf1df63994ea1a579da338e920ad9c27cb2e83073ae4","observation_id":"cc128293-8bb1-4f76-a246-fee82fb1854d","resolution":{"observed_at":"2026-08-10T04:32:43.181500Z","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":"2026-08-10T04:32:43.186212Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.186212Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:c52b74de6ddeb150fab9aec349e9b6008e7c72a8699ebafc6603307b9fc37c02","observation_id":"2f38a6b4-8124-4f92-b2cc-b9f5c7cb186e","resolution":{"observed_at":"2026-08-10T04:32:43.186212Z","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":"2026-08-10T04:32:43.190787Z","title":"Communications of the ACM , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.190787Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:249c3921d2b92fc2801eea2e29f3dcc66babc9015edce4ca60dcf8d6880d3a37","observation_id":"4788874d-027c-4f02-bab3-dc936f1e8f91","resolution":{"observed_at":"2026-08-10T04:32:43.190787Z","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":"2026-08-10T04:32:43.195760Z","title":"Proceedings of the VLDB Endowment , volume=","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.195760Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:ebc1c34144f038ccbead1342dcd5960e77b3de10cdd672026317d4bd21466e71","observation_id":"fd5e3f92-09aa-4957-8c85-e6dd3d80d9a9","resolution":{"observed_at":"2026-08-10T04:32:43.195760Z","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":"2026-08-10T04:32:43.200463Z","title":"IEEE Transactions on Knowledge and Data Engineering , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.200463Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:737e1da29ebc7158c46ecb0b90eaf37be4c75d421c6282486449df2ccfd74231","observation_id":"6aa35da7-6a5a-4dc3-9ccf-01a2d44565ae","resolution":{"observed_at":"2026-08-10T04:32:43.200463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.06229","last_updated":"2018-12-15T03:42:27Z","snapshot_observed_at":"2026-07-06T07:21:19.842962Z","submitted_at":"2018-12-15T03:42:27Z","title":"Domain-to-Domain Translation Model for Recommender System","version":1},"cited_work":{"arxiv_id":"1812.06229","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.06229","snapshot_observed_at":"2026-08-10T04:32:44.355302Z","title":"Domain-to-Domain Translation Model for Recommender System","venue":"cs.IR","work_id":"e6ce3c2f-103b-4b4c-87c7-e0ad2e1a54e3","year":2018},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.205423Z"},"links":{"cited_paper":"/paper/1812.06229","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:c1123668c2ca5b0cfc54b56622aee83e7ec67263f7ff559d2a2dc1533f2067e4","observation_id":"dcebe248-53cd-4b46-a235-a09ecfdd3970","resolution":{"observed_at":"2026-08-10T04:32:44.360711Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:43.210654Z","title":"Journal of Cheminformatics , volume=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.210654Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:2cbe5409d4d52dd0ac6368e750d52ae9165bf3383393cead377386a923190fb7","observation_id":"1ecab51e-6d44-42a5-b7c3-591ba195365a","resolution":{"observed_at":"2026-08-10T04:32:43.210654Z","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":"2026-08-10T04:32:43.215246Z","title":"Conference on learning theory , pages=","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.215246Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:d5b9655773bfb1a1701604ed9a8c48b4ef5b9943b5d7a40ccb63c3894b88268e","observation_id":"ddaa6c47-31fb-44e5-bfeb-64644a33b066","resolution":{"observed_at":"2026-08-10T04:32:43.215246Z","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":"2026-08-10T04:32:43.220012Z","title":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.220012Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:f668ce0c6c9a8bf5b8d6c0389737ba18746304484ddd5ee7e8499075e35d20f3","observation_id":"27a59dc6-d6b3-4a93-8c6c-cbccd9cb4c08","resolution":{"observed_at":"2026-08-10T04:32:43.220012Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.03906","last_updated":"2015-05-14T22:18:42Z","snapshot_observed_at":"2026-07-06T04:17:55.895445Z","submitted_at":"2015-05-14T22:18:42Z","title":"Training generative neural networks via Maximum Mean Discrepancy optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.03906","snapshot_observed_at":"2026-08-10T04:32:43.224515Z","title":"arXiv preprint arXiv:1505.03906 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.224515Z"},"links":{"cited_paper":"/paper/1505.03906","citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:479bef0369eb79001e15901f0887fffa29c7e5663ca5c1b9bff770633eacfb02","observation_id":"d2004def-d193-478c-90e7-00a92c4411d5","resolution":{"observed_at":"2026-08-10T04:32:43.224515Z","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":"2026-08-10T04:32:43.229476Z","title":"International Symposium onInformation Theory, 2004","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.229476Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:1ebf0962f37afbd6b6da030d55d38b0a5165532991781b4672b3e73c98e6cdd2","observation_id":"033b973e-0b09-4c11-8693-ead4f51c0a26","resolution":{"observed_at":"2026-08-10T04:32:43.229476Z","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":"2026-08-10T04:32:43.234020Z","title":"The International Conference on Learning Representations (ICLR 2022) , year=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.234020Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:3b9efb82e47b5598d4d90d810418dcd6d639c213e74dbfb704506ac58b218a1b","observation_id":"f748b92c-ab43-4432-8a50-52cfa707c61b","resolution":{"observed_at":"2026-08-10T04:32:43.234020Z","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":"2026-08-10T04:32:43.238553Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.238553Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:5923aa86a08619721837607806762a07f8675df89f3439f0dc3f791eea19f956","observation_id":"c1a2a95e-74c5-4b4e-8783-63cfc23fc8e2","resolution":{"observed_at":"2026-08-10T04:32:43.238553Z","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":"2026-08-10T04:32:43.242636Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.242636Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b63207f5d60c1bba7f1c253ba19b63497f40575c7f4f69ddae43061854964df1","observation_id":"73d7432c-4d17-42b1-ba53-c03a62d1cab9","resolution":{"observed_at":"2026-08-10T04:32:43.242636Z","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":"2026-08-10T04:32:43.246932Z","title":"Cell reports , volume=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.246932Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b9d0cf8f5eb6bf82834a1326ca5f34e667f96a52b76eec42e9c582ccf33716f3","observation_id":"6a231c86-c20e-4f5c-9fcb-f326eebecd93","resolution":{"observed_at":"2026-08-10T04:32:43.246932Z","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":"2026-08-10T04:32:43.250752Z","title":"A Threshold Selection Method from Gray-Level Histograms , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.250752Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:b09138cc070c3e511d3337bfe67aa16305f79d9c01d3bdff5e97165f4cee59e5","observation_id":"a6c3f9e5-aa6a-41d0-9ca3-ee85e2df1363","resolution":{"observed_at":"2026-08-10T04:32:43.250752Z","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":"2026-08-10T04:32:43.254878Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.254878Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:a0f241932050c6512e80f93f7798234ae5e351c291c1a9db62463923100115f5","observation_id":"cdfe6617-7529-4b35-b35c-9091113bfc6c","resolution":{"observed_at":"2026-08-10T04:32:43.254878Z","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":"2026-08-10T04:32:43.259646Z","title":"International Conference on Machine Learning , pages=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.259646Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:7160ae3685cb76085ee901fe8caacf2249e52db72ff6734955992c31d4438cee","observation_id":"04197d5a-8f37-4709-8e18-a56fa2e21ce6","resolution":{"observed_at":"2026-08-10T04:32:43.259646Z","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":"2026-08-10T04:32:43.263633Z","title":"Medical image analysis , volume=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records","version":1},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-10T04:32:43.263633Z"},"links":{"citing_paper":"/paper/2608.06430"},"observation_digest":"sha256:74ff8d5c49c158709f0cdf7e60e40cd0b3ff3494c72bcacd33768d2e53dbfb56","observation_id":"5e3b5403-6990-4d9d-9be8-ad56d16c8591","resolution":{"observed_at":"2026-08-10T04:32:43.263633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.06430","last_updated":"2026-08-05T23:27:40Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T16:09:56.082760Z","submitted_at":"2026-08-05T23:27:40Z","title":"MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":5,"parse_uncertain":0,"unresolved":88,"verified_exact":7,"verified_fuzzy":0},"total_outbound_references":180},"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 100 of 180 outbound references and 0 inbound Pith citation observations for arXiv:2608.06430."}