Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T05:20:35.075527Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.22264.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T05:20:35.075527Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
42 of 42 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cdd89efb-9a28-41f1-8a2d-b1a2dc496aca · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Layer Normalization
Reference 1
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Observation 235f9d9e-a190-4130-b18e-c4d26644b56a · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=
Reference 2
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Observation fe617a2e-aaaa-4366-996a-3afbe9cccbac · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Proceedings of the 39th International Conference on Machine Learning (ICML) , volume=
Reference 3
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Observation 632b069b-b0a5-4c3f-8980-7bb322c2c98f · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Proceedings of the 39th International Conference on Machine Learning (ICML) , pages=
Reference 4
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Observation 1ccbe544-f5ba-49c2-9a05-7dbc4f11060a · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Proceedings of the 38th International Conference on Machine Learning , series =
Reference 5
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Observation b3b7976b-03cd-4290-9947-809e0825674a · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Advances in Neural Information Processing Systems , editor=
Reference 6
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Observation 0f4057d9-408e-4543-a04e-2f9ac581a054 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs 2020 , eprint =
Reference 7
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Observation ce5cb528-cf20-4bdb-9f02-c1b91d7a0e6d · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) , year =
Reference 8
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Observation 57798d9c-030d-44b7-90c0-fd122fda1cfc · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs OpenAI Technical Report , year =
Reference 9
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Observation 55965b17-796d-4584-89aa-39e5bedfe90a · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Workshop on Time Series Learning for Health (TS4H) at ICLR , year =
Reference 10
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Observation 984d9e28-3705-4d0d-9d2b-cd59e6b7dab7 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs npj Digital Medicine , year =
Reference 11
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Observation c416a91a-a670-49b5-bf5f-d9f5d77d4f18 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs 2024 , publisher =
Reference 12
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Observation 48bf518a-d7d2-4059-bd50-a8509e60b5c7 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs 2023 , publisher =
Reference 13
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Observation 7a747df1-26f4-4014-98fe-ffed9b8e5acd · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Circulation , year =
Reference 14
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Observation 6d993622-2a41-4aed-a26d-de935c8080a0 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Advances in neural information processing systems , volume=
Reference 15
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Observation 29291ba2-5415-460b-bb18-44a79d73da26 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs JAMIA open , volume=
Reference 16
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Observation fbc13d2c-8460-4c58-80f3-07a1741e6baa · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Nature Machine Intelligence , volume=
Reference 17
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Observation 6b7130f9-b676-4a26-89fe-a27799615ab4 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Nature medicine , volume=
Reference 18
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Observation d635d96c-9045-4482-a4e4-1461e9cd57a3 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Journal of biomedical informatics , volume=
Reference 19
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Observation 8b9e5ab6-c0c8-437f-91ff-ee6a9eae6fe3 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Heliyon , volume=
Reference 20
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Observation 605c2ab8-661a-4b0a-8984-73a4ba207586 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Journal of the American Medical Informatics Association , volume=
Reference 21
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Observation 0dad6799-1245-4f84-9f8d-e5b6a909e808 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs MedPatch: Confidence-Guided Multi-Stage Fusion for Multimodal Clinical Data
Reference 22
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Observation a02c5335-8dae-40f2-b1f0-0f9e5a83e2c5 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Authorea Preprints , year=
Reference 23
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Observation 5b05691b-eec6-444b-8e5a-d4bf25d9ac85 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Machine Learning for Health , pages=
Reference 24
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Observation 0be05faf-7f61-4f67-828b-ff1f97501742 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Artificial Intelligence in Medicine , volume=
Reference 25
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Observation 8709c27d-3978-48ac-9a94-3ba01a5f826b · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Briefings in bioinformatics , volume=
Reference 26
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Observation e1fbdaa9-9861-43d3-b4cc-21c70082d6e5 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Scientific Reports , volume=
Reference 27
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Observation 16f88545-1bd4-490f-a82a-9fcf1653685c · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training
Reference 28
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Observation 045a46ae-8275-482d-934c-47121622fe36 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Machine Learning for Health (ML4H) , pages=
Reference 29
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Observation 83af2e64-bec9-4d99-89d3-79b4531c43b6 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Nejm Ai , volume=
Reference 30
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Observation fa9e36c4-a1ca-443b-972a-17e222e6bd09 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs arXiv preprint arXiv:2510.23639 , year=
Reference 31
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Observation e085ff2c-0398-4a93-aa91-9940bea9c5d4 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
Reference 32
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Observation 24c82977-e739-4a87-8f11-fa34fba57ce0 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML
Reference 33
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Observation e19290bc-a845-466a-bb63-d089b6f968f3 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Scientific reports , volume=
Reference 34
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Observation 10099941-bb25-4dba-8523-0bd4f0a3bc13 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs arXiv preprint arXiv:2508.12104 , year=
Reference 35
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Observation 4d3cc7db-0ab0-48a0-ad54-0906663d786f · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Exploring Scaling Laws for EHR Foundation Models
Reference 36
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Observation 8c92d405-327c-41d6-bb3b-7f9572a4d3c0 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Advances in Neural Information Processing Systems , volume=
Reference 37
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Observation 89307e27-5e05-4f42-bccc-275a8aa0fabe · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Type: dataset , volume=
Reference 38
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Observation 2c7c6aed-9d97-43ee-a5c2-9ec889cc5996 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
Reference 39
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Observation b0876ce6-2ac3-4467-aa02-6ce7648970f1 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs PhysioNet , author=
Reference 40
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Observation fedf2872-79b4-4732-bcd3-09fa6f5858a8 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
Reference 41
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Observation 7b2f67e6-5dd4-4681-82f7-7c302062b368 · outbound
Autoregressive EHR Foundation Models with Multimodal Inputs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages=
Reference 42
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No inbound Pith citation observations are available.