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Paper Citation Record · LEDGER

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2601.05353.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2601.05353 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:45:28.728538Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T14:28:07.097169Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T03:57:37.879390Z

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation b8e11601-e5c2-4289-8eff-9a7b0fa046e2 · outbound

This paper cites Diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Diabetes,

Reference 1

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Observation 3d52fded-b53e-4d10-a99d-9f0b44ebfdb3 · outbound

This paper cites Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes,

Reference 2

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Observation afe60b89-9b60-43bd-875f-0e4eaa302293 · outbound

This paper cites Incidence of childhood type 1 diabetes worldwide. diabetes mondiale (diamond) project group.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Incidence of childhood type 1 diabetes worldwide. diabetes mondiale (diamond) project group

Reference 3

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source=pdf_text observed=2026-08-03T11:45:28.630197Z digest=sha256:3ed85c7cdd21e73a2c48a9f9aff6764b682c2bd6c01bc9255bba0cf3efc9f8bb

Observation cb12c690-51fc-4c5f-a350-6d4518ad9d94 · outbound

This paper cites Idf diabetes atlas,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Idf diabetes atlas,

Reference 4

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source=pdf_text observed=2026-08-03T11:45:28.632900Z digest=sha256:eab2e66edd8722531cc30ccf49b6e0f01599cb59d054d11249143447ae832149

Observation ad2d34ac-9558-4099-b73a-c7b2a8f2f36e · outbound

This paper cites Intensive glucose control versus conventional glucose control for type 1 diabetes mellitus,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Intensive glucose control versus conventional glucose control for type 1 diabetes mellitus,

Reference 5

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source=pdf_text observed=2026-08-03T11:45:28.635822Z digest=sha256:011c27e09130cc9970bc0b08101305c71d7b6150c920f3db29138febb5208482

Observation c06c3b90-895e-4b60-9b8c-84b7556192a3 · outbound

This paper cites Trajectories of glycemic change in a national cohort of adults with previously controlled type 2 diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Trajectories of glycemic change in a national cohort of adults with previously controlled type 2 diabetes,

Reference 6

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source=pdf_text observed=2026-08-03T11:45:28.638469Z digest=sha256:61d0abe445bf054258e52910f1ea1ec11b3a3ff34a2226be6caf250f669b3651

Observation 5fe9a5c6-f488-4c2c-af03-e827fb51e922 · outbound

This paper cites Glucose sensor with predictive alarm for hypoglycaemia: Improved glycaemic control in adolescents with type 1 diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Glucose sensor with predictive alarm for hypoglycaemia: Improved glycaemic control in adolescents with type 1 diabetes,

Reference 7

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source=pdf_text observed=2026-08-03T11:45:28.641315Z digest=sha256:9c47a2dcc0a0322f4799a123af9a341485ae64f47044f97d910984a07d97282d

Observation e07d72c2-c4f8-4e1f-af81-431335bbc1cc · outbound

This paper cites Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes,

Reference 8

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source=pdf_text observed=2026-08-03T11:45:28.643776Z digest=sha256:7ff1c0a6d3549cba3bb8a61ff8a658b25a7117c691e086ea2732281a856c235b

Observation ad21a464-0350-4822-94dc-080f477caa98 · outbound

This paper cites Advances in continuous glucose moni- toring: clinical applications,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Advances in continuous glucose moni- toring: clinical applications,

Reference 9

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source=pdf_text observed=2026-08-03T11:45:28.646169Z digest=sha256:1d220ccfe0791d057fcb13e6b2056cb5702a00398023606ee0986af38da042f4

Observation 0d7c10b7-2045-4cf9-9281-e6ea14728a96 · outbound

This paper cites Continuous glucose monitoring sensors for diabetes management: a review of technologies and applications,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Continuous glucose monitoring sensors for diabetes management: a review of technologies and applications,

Reference 10

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source=pdf_text observed=2026-08-03T11:45:28.648604Z digest=sha256:a3b5a087470b780865ea203a29f658f3cbb03cc573243704b50f768a31b8a28e

Observation 0cbe30df-f193-4509-9d86-215252342b38 · outbound

This paper cites GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals

Reference 11

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source=pdf_text observed=2026-08-03T11:45:28.651029Z digest=sha256:c2e24adf092ac4386f16ec3d9354fc36529503ba5499bfcef6865aa5d6b13323

Observation bd7b4160-4282-4376-94cf-21e38bb3c449 · outbound

This paper cites Benchmarking machine learning algorithms on blood glucose prediction for type i diabetes in comparison with classical time-series models,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Benchmarking machine learning algorithms on blood glucose prediction for type i diabetes in comparison with classical time-series models,

Reference 12

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source=pdf_text observed=2026-08-03T11:45:28.653813Z digest=sha256:f0a290f1b217c434885d2e818ffcc1dfc84544097bc1f4c08e0bb6219f707c70

Observation 2feac467-6806-42ed-8793-7c301031fbd0 · outbound

This paper cites Machine learning techniques for hypoglycemia prediction: Trends and challenges,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Machine learning techniques for hypoglycemia prediction: Trends and challenges,

Reference 13

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source=pdf_text observed=2026-08-03T11:45:28.656449Z digest=sha256:8a14c6e2ed014d6e8d2ba067ec2c0c4e24e6623f40b6b17a136944ea23b80b9d

Observation bebdb31b-3961-4fbe-8ab5-eb5764197da5 · outbound

This paper cites Generalized multi task learning framework for glucose forecasting and hypoglycemia detection using simulation to reality,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Generalized multi task learning framework for glucose forecasting and hypoglycemia detection using simulation to reality,

Reference 14

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source=pdf_text observed=2026-08-03T11:45:28.658885Z digest=sha256:e0d665bbc42a78e3df360dbba07504f28ba0dc9da942b907aadb2b5714f792f0

Observation 0d9fd910-b52d-4716-b7e2-43306be087ba · outbound

This paper cites Time-aware cross-attention for multi-modal sensor-based blood glucose forecasting,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Time-aware cross-attention for multi-modal sensor-based blood glucose forecasting,

Reference 15

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source=pdf_text observed=2026-08-03T11:45:28.661204Z digest=sha256:36dbab4bbd00f7376b68bf241d44f1716115a4ad1565a019181fea18421166dc

Observation 7a17e08a-19bb-4d8b-a58d-61434495ba28 · outbound

This paper cites Glunet: A deep learning framework for accurate glucose forecasting,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Glunet: A deep learning framework for accurate glucose forecasting,

Reference 16

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source=pdf_text observed=2026-08-03T11:45:28.663547Z digest=sha256:2115d43b1d7ff86b506ad3b8d0fd761ea748cc64f6e8a54959459694d59595c5

Observation 1161b1ea-f909-4fde-a876-f0177988ffbe · outbound

This paper cites Deep multitask learning by stacked long short-term memory for predicting personalized blood glucose concentration,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Deep multitask learning by stacked long short-term memory for predicting personalized blood glucose concentration,

Reference 17

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source=pdf_text observed=2026-08-03T11:45:28.665934Z digest=sha256:fe3b7bb021e3371d99f76efaab9b0b1f047b7c733c5fed63b335539dca945165

Observation 89fb5801-e884-4f09-8ed1-22d57afb0b2f · outbound

This paper cites A decoder-only foundation model for time-series forecasting,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting A decoder-only foundation model for time-series forecasting,

Reference 18

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source=pdf_text observed=2026-08-03T11:45:28.668329Z digest=sha256:349de6dca0d6add1bfe4d95292bd37e088d10b5d32c7b3c26191ba771fdba87f

Observation 9be6dd2c-46b3-47ce-89fd-9b935e895a6e · outbound

This paper cites Time-LLM: Time series forecasting by reprogramming large language models,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Time-LLM: Time series forecasting by reprogramming large language models,

Reference 19

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source=pdf_text observed=2026-08-03T11:45:28.670758Z digest=sha256:2072a78f49295f9b280ab569d09c2fd9c70ef268352af542fd3382e3e0f956f4

Observation e2c7de19-7467-45e8-9ee8-3e40bfb77def · outbound

This paper cites A deep learning approach for blood glucose prediction of type 1 diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting A deep learning approach for blood glucose prediction of type 1 diabetes,

Reference 20

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source=pdf_text observed=2026-08-03T11:45:28.673146Z digest=sha256:0cb2e932e7d8302d181b494e5cd5983e1444dd085c7cad51a028c8b7f9addeb7

Observation 17b0e088-07ef-41cd-9bac-2cc58690a41a · outbound

This paper cites Long-term prediction of blood glucose levels in type 1 diabetes using a cnn-lstm-based deep neural network,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Long-term prediction of blood glucose levels in type 1 diabetes using a cnn-lstm-based deep neural network,

Reference 21

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source=pdf_text observed=2026-08-03T11:45:28.675637Z digest=sha256:cf209c8bb9d42d1919551e6bf80b4d376462b8d698108bc2877680da9a4cfb33

Observation 41cee238-c9c1-403c-a6c5-f7974f10f1e4 · outbound

This paper cites Integration of clin- ical criteria into the training of deep models: Application to glucose prediction for diabetic people,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Integration of clin- ical criteria into the training of deep models: Application to glucose prediction for diabetic people,

Reference 22

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source=pdf_text observed=2026-08-03T11:45:28.677977Z digest=sha256:6415b4ad223f91f55386a6d55865b2fd667830de8a4d34690d123044c2ac50b9

Observation 1738a263-40ac-456e-b01e-da30552e3e91 · outbound

This paper cites The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using shap,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using shap,

Reference 23

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source=pdf_text observed=2026-08-03T11:45:28.680425Z digest=sha256:568117b4279d5049c55b8472ac8cb82e5fb1cad7f55475c421ca01a0b55638b2

Observation 7d840a89-0cbd-4d42-a800-f6044169ed4b · outbound

This paper cites A multitask learning approach to personalized blood glucose prediction,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting A multitask learning approach to personalized blood glucose prediction,

Reference 24

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source=pdf_text observed=2026-08-03T11:45:28.682803Z digest=sha256:e70f4cc6d95fbfe8ab1b027b6bdcc26dc4b0f74e7476fb991162341122962e54

Observation c16ef992-611a-44b4-87cf-363a3368c776 · outbound

This paper cites Hybrid Attention Model Using Feature Decomposition and Knowledge Distillation for Glucose Forecasting.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Hybrid Attention Model Using Feature Decomposition and Knowledge Distillation for Glucose Forecasting

Reference 25

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source=pdf_text observed=2026-08-03T11:45:28.685191Z digest=sha256:ae225416d11ae250f276d407faadede1f7f511ed63831abef0dd4bec48cfb077

Observation bc8a7b0e-210b-4c67-afdb-60a0b6c27e3d · outbound

This paper cites Timegpt-1,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Timegpt-1,

Reference 26

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source=pdf_text observed=2026-08-03T11:45:28.687954Z digest=sha256:b4c3494698c7128a724de7b17676e8d2921c767cc212afdcb79f5212a8efdeba

Observation b13fc010-8f65-4fa8-acb2-8b418660ff48 · outbound

This paper cites Promptcast: A new prompt-based learning paradigm for time series forecasting,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Promptcast: A new prompt-based learning paradigm for time series forecasting,

Reference 27

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source=pdf_text observed=2026-08-03T11:45:28.690477Z digest=sha256:9679abc1cc183b9b6293f63f538a6f01940397da0f0e026d72085cd6eb38182f

Observation c353e3be-38d1-4854-9b18-45950c70842c · outbound

This paper cites Large Language Models are Few-Shot Health Learners.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Large Language Models are Few-Shot Health Learners

Reference 28

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source=pdf_text observed=2026-08-03T11:45:28.692829Z digest=sha256:54cd95efc0fd36d52d9e132447857c05af5bf29bdf2b9b32f95cf50b846e5a98

Observation 8b801796-3bd7-4f95-8c8c-0d83fe279aa3 · outbound

This paper cites Timecap: Learning to contextualize, augment, and predict time series events with large language model agents,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Timecap: Learning to contextualize, augment, and predict time series events with large language model agents,

Reference 29

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source=pdf_text observed=2026-08-03T11:45:28.695610Z digest=sha256:2ffff12aee4b07687afc62d1fac2e3c19ef4794aa69725b67a9b2c46c0c52a2c

Observation 3e349b90-ec71-4b34-afa5-b126ad1d8e9f · outbound

This paper cites Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Reference 30

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Observation f6c2f17f-4d07-460d-8b5a-0318a828880f · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 31

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Observation cf11938d-e93e-4e7b-92c9-dd9d86b24d6a · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting A time series is worth 64 words: Long-term forecasting with transformers,

Reference 32

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Observation be53ff27-ea16-4847-81e1-db74ae695efc · outbound

This paper cites The ohiot1dm dataset for blood glucose level prediction: Update 2020,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting The ohiot1dm dataset for blood glucose level prediction: Update 2020,

Reference 33

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Observation 4fecca97-fec3-4400-b707-cb4e8bb10d8a · outbound

This paper cites Azt1d: A real-world dataset for type 1 diabetes,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Azt1d: A real-world dataset for type 1 diabetes,

Reference 34

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source=pdf_text observed=2026-08-03T11:45:28.710672Z digest=sha256:96b52ef92a6fcc42d259a0a7c096df7c26659db07b23f48212c44f6c14575cd8

Observation fd1b875d-b131-4a6b-a010-6a26275b8d42 · outbound

This paper cites Blood glucose prediction with variance estimation using recurrent neural networks,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Blood glucose prediction with variance estimation using recurrent neural networks,

Reference 35

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source=pdf_text observed=2026-08-03T11:45:28.713193Z digest=sha256:8bf0abb9025d753bab390b177cabbaac906e1d9673f647417930b8e7883f17a8

Observation d391a0c1-7974-40ba-84db-4d2f38356988 · outbound

This paper cites Deep residual time-series forecasting: Application to blood glucose prediction.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Deep residual time-series forecasting: Application to blood glucose prediction

Reference 36

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Observation 4cf5a919-32ca-400d-9408-ac6f75bbb500 · outbound

This paper cites Investigating potentials and pitfalls of knowledge distillation across datasets for blood glucose forecasting,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Investigating potentials and pitfalls of knowledge distillation across datasets for blood glucose forecasting,

Reference 37

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Observation 924d7485-e822-4b0c-91df-4bb2976d75ff · outbound

This paper cites Personalised short-term glucose prediction via recurrent self-attention network,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Personalised short-term glucose prediction via recurrent self-attention network,

Reference 38

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Observation 0fb603e0-37e2-4ee2-ba07-bb7028eec741 · outbound

This paper cites Glysim: Modeling and simulating glycemic response for behavioral lifestyle interventions,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Glysim: Modeling and simulating glycemic response for behavioral lifestyle interventions,

Reference 39

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Observation 3a32bdba-9cf3-46a3-a165-ebf6f7ad4713 · outbound

This paper cites Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes

Reference 40

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Observation 6445dd13-3892-4ace-8ceb-76fc84733485 · outbound

This paper cites Evaluating clinical accuracy of systems for self-monitoring of blood glucose,.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Evaluating clinical accuracy of systems for self-monitoring of blood glucose,

Reference 41

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Observation fee0bfea-5602-4def-9818-ff4ef10bda6f · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 52967399.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Available: https://api.semanticscholar.org/CorpusID: 52967399

Reference 2019

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Pith citing papers

Observation df7037f7-c9f5-41d7-986d-59189a669c33 · inbound

MetaPlate: Counterfactual-Guided RAG-LLM Tool for Personalized Food Recommendation and Hyperglycemia Prevention cites this paper.

MetaPlate: Counterfactual-Guided RAG-LLM Tool for Personalized Food Recommendation and Hyperglycemia Prevention GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting

Reference 23

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