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Paper Citation Record · LEDGER

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark

As of 10 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2606.30027.

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

pith.paper-citation-record.v1
2606.30027 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T06:22:26.703257Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

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  • verified fuzzy0
  • unresolved17
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation 5a3c8e27-92bd-444b-abd6-8984b779f9bc · outbound

This paper cites Systematic comparison of deep-learning based fusion strategies for multi-modal ultrasound in diagnosis of liver cancer,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Systematic comparison of deep-learning based fusion strategies for multi-modal ultrasound in diagnosis of liver cancer,

Reference 1

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Observation 35bb18a2-252a-4b1a-af73-3b4a6b81ba40 · outbound

This paper cites Retinal vessel calibre and risk for coronary heart disease: a systematic review and meta-analysis,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Retinal vessel calibre and risk for coronary heart disease: a systematic review and meta-analysis,

Reference 2

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Observation 180adff5-10ff-4f3f-9657-c34756bfc6ce · outbound

This paper cites A foundation model for generalizable disease detection from retinal images,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark A foundation model for generalizable disease detection from retinal images,

Reference 3

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Observation 5dd49f2d-fa53-4edf-bf77-31cd371fbec8 · outbound

This paper cites Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases,

Reference 4

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source=pdf_text observed=2026-06-30T06:22:26.703257Z digest=sha256:3063875207b61f312d2858f15778011ad6fcd6ac396fd946caed4f302333fc60

Observation 62ca340c-c247-4a05-b8ff-90a714ac9d36 · outbound

This paper cites Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning,

Reference 5

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Observation fa3a37bb-e30c-41a8-8f16-5a3eace05e9a · outbound

This paper cites A review of diabetic retinopathy: Datasets, approaches, evaluation metrics and future trends,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark A review of diabetic retinopathy: Datasets, approaches, evaluation metrics and future trends,

Reference 6

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source=pdf_text observed=2026-06-30T06:22:26.703257Z digest=sha256:394e5394618006b0a550e9643f6cbfcd10e60ba89e0f11cc433933c9dfd7d984

Observation 042791fd-b406-49d4-b56c-644350d5775a · outbound

This paper cites Focal loss for dense object detection,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Focal loss for dense object detection,

Reference 7

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Observation 802cbc0f-562c-48e0-93cc-ed0385c6a073 · outbound

This paper cites Supervised contrastive learning,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Supervised contrastive learning,

Reference 8

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Observation 681ffe56-bdec-4261-80c1-c7c4c15792fa · outbound

This paper cites Mil-vit: A multiple instance vision transformer for fundus image classification,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Mil-vit: A multiple instance vision transformer for fundus image classification,

Reference 9

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Observation 440e0d7e-db16-499b-a83f-f17d8b6eff46 · outbound

This paper cites Mstnet: Multi-scale spatial- aware transformer with multi-instance learning for diabetic retinopathy classification,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Mstnet: Multi-scale spatial- aware transformer with multi-instance learning for diabetic retinopathy classification,

Reference 10

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Observation d542d843-362a-424e-8f55-07385acf5462 · outbound

This paper cites Multimodal co- attention transformer for survival prediction in gigapixel whole slide images,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Multimodal co- attention transformer for survival prediction in gigapixel whole slide images,

Reference 11

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Observation fe82f2f1-f008-44b6-a64f-88ae6a083e8d · outbound

This paper cites Multimodal optimal transport-based co- attention transformer with global structure consistency for survival prediction,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Multimodal optimal transport-based co- attention transformer with global structure consistency for survival prediction,

Reference 12

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Observation adb5159c-7eb8-44eb-9b33-dc6997856c02 · outbound

This paper cites Heal- net: Multimodal fusion for heterogeneous biomedical data,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Heal- net: Multimodal fusion for heterogeneous biomedical data,

Reference 13

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Observation 920580c9-6283-4e37-8c11-86af826e4839 · outbound

This paper cites Deep residual learning for image recognition,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Deep residual learning for image recognition,

Reference 14

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Observation c2657370-7538-4cdd-bd6d-34c0bce93256 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 15

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local_arxiv, observed 2026-06-30T06:24:18.897874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T06:22:26.703257Z digest=sha256:d43794c302be560acb0002ad6bfe7116935fed484233222e7c7d1404d32047db

Observation a2d2d503-9b52-4505-8b5c-cbfa55168c5c · outbound

This paper cites Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures

Reference 16

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arxiv_id, observed 2026-06-30T06:24:18.900350Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1ba7a8a6-a5ad-44c0-a8fe-c1b226ce934b · outbound

This paper cites Vision mamba: A comprehensive survey and taxonomy,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Vision mamba: A comprehensive survey and taxonomy,

Reference 17

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Observation bda55631-b4c1-4542-a1ce-96e11c0762fc · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 18

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Observation 2d442c9f-74f8-4188-93e6-527386afd77a · outbound

This paper cites Convnext v2: Co- designing and scaling convnets with masked autoencoders,.

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark Convnext v2: Co- designing and scaling convnets with masked autoencoders,

Reference 19

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Pith citing papers

No inbound Pith citation observations are available.