Paper Citation Record · LEDGER

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images

As of 15 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2412.09402.

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

pith.paper-citation-record.v1
2412.09402 v2

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Outbound references

Observation 35cd55ea-93ef-47a9-8933-297ae0f18e50 · outbound

This paper cites Digital ocular fundus imaging: a review,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Digital ocular fundus imaging: a review,

Reference 1

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Observation af8b5839-9d8f-409f-8710-5f7a8791c4d4 · outbound

This paper cites Review of oct and fundus images for detection of macular edema,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Review of oct and fundus images for detection of macular edema,

Reference 2

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Observation 99a2edd0-eb4e-4fc0-b34d-73535d73a4aa · outbound

This paper cites Combining optical coherence tomography and fundus photography to improve glaucoma screening,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Combining optical coherence tomography and fundus photography to improve glaucoma screening,

Reference 3

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Observation 43561a46-5e7a-4abd-8524-bc887e943028 · outbound

This paper cites Value of combining optical coherence to- mography with fundus photography in screening retinopathy in patients with high myopia,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Value of combining optical coherence to- mography with fundus photography in screening retinopathy in patients with high myopia,

Reference 4

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Observation 2121e778-c02a-4df5-918a-da917bae7ce9 · outbound

This paper cites Fundus-enhanced disease- aware distillation model for retinal disease classification from oct images,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Fundus-enhanced disease- aware distillation model for retinal disease classification from oct images,

Reference 5

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Observation 96d04d57-a63d-4368-9ae8-0a601db45266 · outbound

This paper cites The possibility of the combination of oct and fundus images for improving the diagnostic accuracy of deep learning for age- related macular degeneration: a preliminary experiment,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images The possibility of the combination of oct and fundus images for improving the diagnostic accuracy of deep learning for age- related macular degeneration: a preliminary experiment,

Reference 6

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Observation 737e4b5b-4449-4b3f-b444-4ed9f62da234 · outbound

This paper cites Two-stream cnn with loose pair training for multi-modal amd categorization,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Two-stream cnn with loose pair training for multi-modal amd categorization,

Reference 7

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Observation fa2a48a6-4738-412f-98ea-f5512b1e4c51 · outbound

This paper cites Multi-modal multi-instance learning for retinal disease recognition,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Multi-modal multi-instance learning for retinal disease recognition,

Reference 8

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Observation 6a39cd26-ffd0-46a7-a0e3-2fd466658f23 · outbound

This paper cites Multimodal information fusion for glaucoma and diabetic retinopathy classification,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Multimodal information fusion for glaucoma and diabetic retinopathy classification,

Reference 9

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Observation 9ba3490b-05a6-42c2-af56-7fa680b81163 · outbound

This paper cites Learn- ing two-stream cnn for multi-modal age-related macular degeneration categorization,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Learn- ing two-stream cnn for multi-modal age-related macular degeneration categorization,

Reference 10

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Observation 4a586fd5-8dfe-4ea1-8b82-ecb3e42add18 · outbound

This paper cites A composite retinal fundus and oct dataset to grade macular and glaucomatous disorders,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images A composite retinal fundus and oct dataset to grade macular and glaucomatous disorders,

Reference 11

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This paper cites Optical coherence tomog- raphy in the 2020s—outside the eye clinic,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Optical coherence tomog- raphy in the 2020s—outside the eye clinic,

Reference 12

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Observation 48b52fd8-86ae-4eee-9714-1b87c17b2ea9 · outbound

This paper cites Ophthalmic diagnostic imaging: retina,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Ophthalmic diagnostic imaging: retina,

Reference 13

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Observation aefb7711-173b-4d27-87b3-ac1b17cf91c5 · outbound

This paper cites Optical coherence tomography and color fundus photography in the screening of age-related macular degeneration: A comparative, population-based study,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Optical coherence tomography and color fundus photography in the screening of age-related macular degeneration: A comparative, population-based study,

Reference 14

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Observation 98f24159-19a2-43e1-b405-51bb714041da · outbound

This paper cites Comparison of time-domain oct and fundus photographic assessments of retinal thickening in eyes with diabetic macular edema,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Comparison of time-domain oct and fundus photographic assessments of retinal thickening in eyes with diabetic macular edema,

Reference 15

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Observation acb33792-d968-4203-9bf1-427be4b91365 · outbound

This paper cites Multi-modal retinal image clas- sification with modality-specific attention network,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Multi-modal retinal image clas- sification with modality-specific attention network,

Reference 16

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This paper cites Language mod- els are few-shot learners,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Language mod- els are few-shot learners,

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This paper cites GPT-4 Technical Report.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images GPT-4 Technical Report

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This paper cites Learning transferable visual models from natural language supervision,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Learning transferable visual models from natural language supervision,

Reference 19

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This paper cites A Foundation Language-Image Model of the Retina (FLAIR): Encoding Expert Knowledge in Text Supervision.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images A Foundation Language-Image Model of the Retina (FLAIR): Encoding Expert Knowledge in Text Supervision

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This paper cites Visual Classification via Description from Large Language Models.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Visual Classification via Description from Large Language Models

Reference 21

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This paper cites What does a platypus look like? generating customized prompts for zero-shot image classification,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images What does a platypus look like? generating customized prompts for zero-shot image classification,

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This paper cites Text Descriptions are Compressive and Invariant Representations for Visual Learning.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Text Descriptions are Compressive and Invariant Representations for Visual Learning

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This paper cites A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis

Reference 24

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This paper cites Language in a bottle: Language model guided concept bottlenecks for interpretable image classification,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Language in a bottle: Language model guided concept bottlenecks for interpretable image classification,

Reference 25

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Label-Free Concept Bottleneck Models

Reference 26

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This paper cites LLMs as Visual Explainers: Advancing Image Classification with Evolving Visual Descriptions.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images LLMs as Visual Explainers: Advancing Image Classification with Evolving Visual Descriptions

Reference 27

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This paper cites Concept bottleneck with visual concept filtering for explainable medical image classification,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Concept bottleneck with visual concept filtering for explainable medical image classification,

Reference 28

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This paper cites Few-shot medical image classification with simple shape and texture text descriptors using vision-language models.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Few-shot medical image classification with simple shape and texture text descriptors using vision-language models

Reference 29

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This paper cites Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models

Reference 30

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This paper cites Distilling the Knowledge in a Neural Network.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Distilling the Knowledge in a Neural Network

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Cross modal distillation for supervision transfer,

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This paper cites Learning deep representations with proba- bilistic knowledge transfer,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Learning deep representations with proba- bilistic knowledge transfer,

Reference 33

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Distilling audio- visual knowledge by compositional contrastive learning,

Reference 34

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Unpaired cross- modality educed distillation (cmedl) for medical image segmentation,

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This paper cites Learning with privileged multimodal knowledge for unimodal segmentation,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Learning with privileged multimodal knowledge for unimodal segmentation,

Reference 36

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This paper cites Asynchronous feature regularization and cross-modal distillation for oct based glaucoma diagnosis,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Asynchronous feature regularization and cross-modal distillation for oct based glaucoma diagnosis,

Reference 37

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Chain-of-thought prompting elicits reasoning in large language models,

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This paper cites Retinal fundus multi-disease image dataset (rfmid),.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Retinal fundus multi-disease image dataset (rfmid),

Reference 39

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Retinal fundus multi-disease image dataset (rfmid) 2.0,

Reference 40

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This paper cites Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks,

Reference 41

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This paper cites Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators,

Reference 42

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This paper cites Fives: A fundus image dataset for artificial intelligence based vessel segmentation,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Fives: A fundus image dataset for artificial intelligence based vessel segmentation,

Reference 43

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This paper cites Diagnostic as- sessment of deep learning algorithms for diabetic retinopathy screening,.

MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Diagnostic as- sessment of deep learning algorithms for diabetic retinopathy screening,

Reference 44

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Octid: Optical coherence tomography image database,

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Dataset and evalu- ation algorithm design for goals challenge,

Reference 46

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images Cross attentional audio- visual fusion for dimensional emotion recognition,

Reference 47

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MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images A joint cross-attention model for audio-visual fusion in dimensional emotion recognition,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:09:45.049767Z

Source-reported events for the cited work

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Pith citing papers

Observation 123653cf-1951-45a1-a89f-e67ff993bd4c · inbound

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy cites this paper.

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-11T22:45:34.273188Z

Source-reported events for the cited work

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