Federated generative event models for tokenized electronic health records | Paper Citation Record

Observation 89753d85-44b4-45da-8c3c-d32919a1e291 · outbound

This paper cites Scaling Laws for Neural Language Models.

Federated generative event models for tokenized electronic health records Scaling Laws for Neural Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.832079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f269ffc7-673d-410e-91d6-986784ee3723 · outbound

This paper cites An empirical analysis of compute-optimal large language model training,.

Federated generative event models for tokenized electronic health records An empirical analysis of compute-optimal large language model training,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.871039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7c996e08-face-4e58-b75c-c2f93590832e · outbound

This paper cites Exploring Scaling Laws for EHR Foundation Models.

Federated generative event models for tokenized electronic health records Exploring Scaling Laws for EHR Foundation Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.840760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09b6236a-dfe7-4252-8cff-bb7385ca03e7 · outbound

This paper cites Generative medical event models improve with scale.

Federated generative event models for tokenized electronic health records Generative medical event models improve with scale

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.844665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6deaedd-ad76-4a06-bf2d-e9dfdbffe99f · outbound

This paper cites A multi-center study on the adaptability of a shared foundation model for electronic health records,.

Federated generative event models for tokenized electronic health records A multi-center study on the adaptability of a shared foundation model for electronic health records,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.861007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d5c6a4e1-9378-4d87-966b-262d16c67acf · outbound

This paper cites Foundation models for electronic health records: representation dynamics and transferability.

Federated generative event models for tokenized electronic health records Foundation models for electronic health records: representation dynamics and transferability

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.852683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c8e6723-8f66-4200-b7dd-4fabbd959b31 · outbound

This paper cites FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records.

Federated generative event models for tokenized electronic health records FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.856932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5adf6377-5123-4250-ae8d-788ec9fc4a04 · outbound

This paper cites Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2),.

Federated generative event models for tokenized electronic health records Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2),

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.850179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0d46f084-9d89-4ef0-8f37-877323aaf431 · outbound

This paper cites Feasibility and utility of applications of the common data model to multiple, disparate observational health databases,.

Federated generative event models for tokenized electronic health records Feasibility and utility of applications of the common data model to multiple, disparate observational health databases,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.840787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f9b6b779-1060-4e86-a558-6c108a781889 · outbound

This paper cites Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data,.

Federated generative event models for tokenized electronic health records Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.830305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dfa1d6f1-5f22-49e8-9749-4e2fcbea3402 · outbound

This paper cites Representation learning to advance multi-institutional studies with electronic health record data from US and France,.

Federated generative event models for tokenized electronic health records Representation learning to advance multi-institutional studies with electronic health record data from US and France,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.819657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f55dee5b-61f1-4735-845a-4ee596341956 · outbound

This paper cites Trends in ransomware attacks on US hospitals, clinics, and other health care delivery organizations, 2016-2021,.

Federated generative event models for tokenized electronic health records Trends in ransomware attacks on US hospitals, clinics, and other health care delivery organizations, 2016-2021,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.809789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a6e539f8-7c6e-4103-9e00-080ca55e19ab · outbound

This paper cites Ransomware attacks and data breaches in US health care systems,.

Federated generative event models for tokenized electronic health records Ransomware attacks and data breaches in US health care systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.799583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 89199677-77e0-42d4-a625-4c8b614bbffb · outbound

This paper cites A common longitudinal intensive care unit data format (CLIF) for critical illness research,.

Federated generative event models for tokenized electronic health records A common longitudinal intensive care unit data format (CLIF) for critical illness research,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.789596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e7ceaff2-9e70-4d12-8ef4-97c3db3f9b3b · outbound

This paper cites Federation, not centralization: a new paradigm for electronic health record–based critical care research,.

Federated generative event models for tokenized electronic health records Federation, not centralization: a new paradigm for electronic health record–based critical care research,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.780488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3dbc376f-1b84-4dc1-bacd-4080d414e5a1 · outbound

This paper cites Quantifying surprise in clinical care: Detecting highly informative events in electronic health records with foundation models,.

Federated generative event models for tokenized electronic health records Quantifying surprise in clinical care: Detecting highly informative events in electronic health records with foundation models,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.771215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f02348b7-475d-4b53-a595-f5a2a4469b7e · outbound

This paper cites EveryQuery: Zero-Shot Clinical Prediction via Task-Conditioned Pretraining over Electronic Health Records.

Federated generative event models for tokenized electronic health records EveryQuery: Zero-Shot Clinical Prediction via Task-Conditioned Pretraining over Electronic Health Records

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:00:17.304027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 14181446-8ec7-4e8d-981e-581011ff188d · outbound

This paper cites Systematic review of foundation models for structured electronic health records,.

Federated generative event models for tokenized electronic health records Systematic review of foundation models for structured electronic health records,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.759539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3075e698-850e-48fb-9eee-e47f6bbd16f8 · outbound

This paper cites EHRSHOT: An EHR benchmark for few-shot evaluation of foundation models,.

Federated generative event models for tokenized electronic health records EHRSHOT: An EHR benchmark for few-shot evaluation of foundation models,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.748813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1bf4067f-23bb-441e-a37a-89807e640bd4 · outbound

This paper cites Context clues: Evaluating long context models for clinical prediction tasks on EHRs,.

Federated generative event models for tokenized electronic health records Context clues: Evaluating long context models for clinical prediction tasks on EHRs,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.738894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 08366514-f0c3-41fb-b14a-3c3c1b9dc6cc · outbound

This paper cites Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models.

Federated generative event models for tokenized electronic health records Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:00:17.287481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 08b32143-e5c6-4720-bd94-89c6856ad1c3 · outbound

This paper cites Tokenization tradeoffs in structured EHR foundation models.

Federated generative event models for tokenized electronic health records Tokenization tradeoffs in structured EHR foundation models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.907081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd61bd3f-4eac-42a1-aff3-4445f3bbeffb · outbound

This paper cites A multimodal and temporal foundation model for virtual patient representations at healthcare system scale.

Federated generative event models for tokenized electronic health records A multimodal and temporal foundation model for virtual patient representations at healthcare system scale

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:16.910214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66279d5f-bf03-483b-8553-0d3fa3216ebf · outbound

This paper cites Event stream GPT: A data pre-processing and modeling library for generative, pre-trained transformers over continuous-time sequences of complex events,.

Federated generative event models for tokenized electronic health records Event stream GPT: A data pre-processing and modeling library for generative, pre-trained transformers over continuous-time sequences of complex events,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.729507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 138aa47f-8f26-46c3-ba6c-3162dff04f57 · outbound

This paper cites Foresight-a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study,.

Federated generative event models for tokenized electronic health records Foresight-a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.719473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 50cd99ef-bd26-4aee-a4ab-e122f2136301 · outbound

This paper cites Zero shot health trajectory prediction using transformer,.

Federated generative event models for tokenized electronic health records Zero shot health trajectory prediction using transformer,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.707881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9826e6c1-dd4d-4729-88d3-a8597636b90e · outbound

This paper cites Foundation model of electronic medical records for adaptive risk estimation,.

Federated generative event models for tokenized electronic health records Foundation model of electronic medical records for adaptive risk estimation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.697646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d360eb5e-8c84-4669-a6fa-12f738f2df1a · outbound

This paper cites Efficient Generative Prediction for EHR Foundation Models: The SCOPE and REACH Estimators.

Federated generative event models for tokenized electronic health records Efficient Generative Prediction for EHR Foundation Models: The SCOPE and REACH Estimators

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:00:17.202805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 108ff9d5-c74d-4281-8762-e0e06e221fc8 · outbound

This paper cites MOTOR: A time-to-event foundation model for structured medical records,.

Federated generative event models for tokenized electronic health records MOTOR: A time-to-event foundation model for structured medical records,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.687983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 25b576d1-ef50-497f-aa7b-e467543c16f5 · outbound

This paper cites EHRMamba: Towards generalizable and scalable foundation models for electronic health records,.

Federated generative event models for tokenized electronic health records EHRMamba: Towards generalizable and scalable foundation models for electronic health records,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.679104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a39f8bf1-b513-4137-88c0-bf1246a2db1b · outbound

This paper cites Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture,.

Federated generative event models for tokenized electronic health records Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.669976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2b58f453-640f-4b50-9b66-759ab44c5a59 · outbound

This paper cites Federated learning authenticity standard for healthcare as derived from lessons in self-driving cars,.

Federated generative event models for tokenized electronic health records Federated learning authenticity standard for healthcare as derived from lessons in self-driving cars,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.659219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a81608c7-95bf-4b3b-afeb-749b5c0114a7 · outbound

This paper cites MIMIC-IV, a freely accessible electronic health record dataset,.

Federated generative event models for tokenized electronic health records MIMIC-IV, a freely accessible electronic health record dataset,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.648792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1f1f6281-3b66-4a29-948d-e7624a38c20e · outbound

This paper cites The eICU collaborative research database, a freely available multi-center database for critical care research,.

Federated generative event models for tokenized electronic health records The eICU collaborative research database, a freely available multi-center database for critical care research,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.639954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3219734e-94c1-438d-848f-2a5cefac8d64 · outbound

This paper cites Federated learning for electronic health records,.

Federated generative event models for tokenized electronic health records Federated learning for electronic health records,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.628827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8472f9b5-6089-4ec1-8646-ef1da9f0c1c4 · outbound

This paper cites Communication- efficient learning of deep networks from decentralized data,.

Federated generative event models for tokenized electronic health records Communication- efficient learning of deep networks from decentralized data,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.618659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2673cc38-c322-40a9-84ec-72154f3f5d50 · outbound

This paper cites Measuring the effects of non-identical data distribution for federated visual classification,.

Federated generative event models for tokenized electronic health records Measuring the effects of non-identical data distribution for federated visual classification,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.606068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 58e6d4ce-6597-42e5-892c-a5b65334c999 · outbound

This paper cites Federated learning of medical concepts embedding using BEHRT,.

Federated generative event models for tokenized electronic health records Federated learning of medical concepts embedding using BEHRT,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.595769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d5f6098c-9058-4403-a40b-136d204341cc · outbound

This paper cites Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment.

Federated generative event models for tokenized electronic health records Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:00:17.189434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ce54d6f9-7933-4aae-85d9-61570d142f3a · outbound

This paper cites Validation of a common data model for active safety surveillance research,.

Federated generative event models for tokenized electronic health records Validation of a common data model for active safety surveillance research,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.585597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5e2188eb-a0ab-4e15-9638-2351640ae229 · outbound

This paper cites Federated learning for heterogeneous electronic health record systems with cost effective participant selection.

Federated generative event models for tokenized electronic health records Federated learning for heterogeneous electronic health record systems with cost effective participant selection

Reference 41

Resolution: verified exact; raw_fallback, observed 2026-08-15T15:00:17.173594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6b0118ef-89df-40dc-9133-7c9d18914c6a · outbound

This paper cites PORTER: Language-Grounded Event Representations for Portable Structured EHR Foundation Models.

Federated generative event models for tokenized electronic health records PORTER: Language-Grounded Event Representations for Portable Structured EHR Foundation Models

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:00:17.105633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b5e3c6ab-e801-4497-96ae-45f43f201ae6 · outbound

This paper cites Representation learning of structured data for medical foundation models,.

Federated generative event models for tokenized electronic health records Representation learning of structured data for medical foundation models,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.574981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 17a7ebce-926c-4df6-974c-ff0b173d33bf · outbound

This paper cites Continuous kidney replacement therapies: Core curriculum 2025,.

Federated generative event models for tokenized electronic health records Continuous kidney replacement therapies: Core curriculum 2025,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.565602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f4ed2bce-fe48-409f-90b2-95c7873d05a0 · outbound

This paper cites Hohmann, F.

Federated generative event models for tokenized electronic health records Hohmann, F

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.554210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97008fbb-8b8f-4406-86b7-e501bf4b23d0 · outbound

This paper cites Association between do not resuscitate/do not intubate status and resident physician decision-making: A national survey,.

Federated generative event models for tokenized electronic health records Association between do not resuscitate/do not intubate status and resident physician decision-making: A national survey,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.543245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a5e74c3e-5d9b-4eba-a089-19e3490c30cc · outbound

This paper cites Prone position in ARDS patients: why, when, how and for whom,.

Federated generative event models for tokenized electronic health records Prone position in ARDS patients: why, when, how and for whom,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.533215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e9b2ccda-85fc-47c0-acc2-511569f2be74 · outbound

This paper cites The third international consensus definitions for sepsis and septic shock (Sepsis-3),.

Federated generative event models for tokenized electronic health records The third international consensus definitions for sepsis and septic shock (Sepsis-3),

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.521955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 36a63889-e92b-4bbf-9b5f-e2e1a67584c6 · outbound

This paper cites CEHR- BERT: Incorporating temporal information from structured EHR data to improve prediction tasks,.

Federated generative event models for tokenized electronic health records CEHR- BERT: Incorporating temporal information from structured EHR data to improve prediction tasks,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.511386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f4100b7e-e580-465e-a536-1053a7c435b7 · outbound

This paper cites Rethinking tokenization for clinical time series: When less is more,.

Federated generative event models for tokenized electronic health records Rethinking tokenization for clinical time series: When less is more,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.502095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f2bb93ba-d7e1-4d38-be38-6584d1f79117 · outbound

This paper cites The Llama 3 Herd of Models.

Federated generative event models for tokenized electronic health records The Llama 3 Herd of Models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:17.006934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcf740df-f9f8-41c2-aed9-7d58fd1ea5ce · outbound

This paper cites Decoupled weight decay regularization,.

Federated generative event models for tokenized electronic health records Decoupled weight decay regularization,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:17.010769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ded132c-2e85-43e5-a48f-7d3e92fecede · outbound

This paper cites Adam: A method for stochastic optimization,.

Federated generative event models for tokenized electronic health records Adam: A method for stochastic optimization,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:17.014727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0834f85-ac4a-4d6f-b38b-2113071729e4 · outbound

This paper cites Comparing biases for minimal network construction with back- propagation,.

Federated generative event models for tokenized electronic health records Comparing biases for minimal network construction with back- propagation,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.480780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4df512e-96ec-44e2-9010-f7852cfbcd72 · outbound

This paper cites RoFormer: Enhanced transformer with rotary position embedding,.

Federated generative event models for tokenized electronic health records RoFormer: Enhanced transformer with rotary position embedding,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.471121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1c3c645f-b41a-40c1-9963-1c41223d3665 · outbound

This paper cites NEFTune: Noisy embeddings improve instruction finetuning,.

Federated generative event models for tokenized electronic health records NEFTune: Noisy embeddings improve instruction finetuning,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.460228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d4ab9e3-7683-4b23-b679-2c8a58fd18e8 · outbound

This paper cites A method of solving a convex programming problem with convergence rate o(1/sqr(k)),.

Federated generative event models for tokenized electronic health records A method of solving a convex programming problem with convergence rate o(1/sqr(k)),

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.448436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 25adb77e-9e47-4546-8274-59bf9db4e36c · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

Federated generative event models for tokenized electronic health records Flower: A Friendly Federated Learning Research Framework

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T15:00:17.032931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d1e236d-c659-4fab-b34e-8124044c1475 · outbound

This paper cites Some methods of speeding up the convergence of iteration methods,.

Federated generative event models for tokenized electronic health records Some methods of speeding up the convergence of iteration methods,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.437620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 50dc6c6e-344d-41f2-a895-244ae595d412 · outbound

This paper cites Adaptive federated optimization,.

Federated generative event models for tokenized electronic health records Adaptive federated optimization,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.427198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9603b42c-9368-47e5-86f8-9a47a8b6eed4 · outbound

This paper cites A closer look at AUROC and AUPRC under class imbalance,.

Federated generative event models for tokenized electronic health records A closer look at AUROC and AUPRC under class imbalance,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.416251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation af04e89f-69ad-448e-a0c0-23ded7c817cc · outbound

This paper cites Efron and R.

Federated generative event models for tokenized electronic health records Efron and R

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.404889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation decc1a57-5251-4d07-b318-b0f690e0e347 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree,.

Federated generative event models for tokenized electronic health records Lightgbm: A highly efficient gradient boosting decision tree,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.395418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d131b74a-4c06-4f4b-85e4-5cea5e78a746 · outbound

This paper cites Physiobank, physiotoolkit, and physionet,.

Federated generative event models for tokenized electronic health records Physiobank, physiotoolkit, and physionet,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:00:17.384968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers