Paper Citation Record · LEDGER

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification

As of 15 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2505.24792.

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

pith.paper-citation-record.v1
2505.24792 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:19:18.567764Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

29 of 29 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b65d162-692a-4318-b614-34f686f27084 · outbound

This paper cites A novel multi-feature fusion method for classification of gastrointestinal diseases using endoscopy images,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification A novel multi-feature fusion method for classification of gastrointestinal diseases using endoscopy images,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:22.717505Z

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Observation c9829ed8-0834-4e19-8e5d-b6e5a172c05a · outbound

This paper cites Automatic detection and segmentation of colorectal cancer with deep residual convolutional neural net- work,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Automatic detection and segmentation of colorectal cancer with deep residual convolutional neural net- work,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:22.540825Z

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Observation c37c7a22-caf9-485e-b59c-f9909fcb55f0 · outbound

This paper cites Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video),.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video),

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:22.354483Z

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Observation 941b11b3-726d-4018-b58c-9170990b83cf · outbound

This paper cites A Combined Corner and Edge Detector,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification A Combined Corner and Edge Detector,

Reference 4

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Observation 2a179667-55cc-4f91-9074-6959d862a880 · outbound

This paper cites Surf: Speeded up robust features,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Surf: Speeded up robust features,

Reference 5

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Observation 7bb78dd9-4ed8-4810-9fc9-3d36c5038331 · outbound

This paper cites Orb: An efficient alternative to sift or surf,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Orb: An efficient alternative to sift or surf,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:21.822138Z

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Observation dc1dcba4-557c-4805-867a-1cc81c329832 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 7

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Observation e53da4e3-1fc8-4142-baed-5a0a6bd9adee · outbound

This paper cites Efficient detection of lesions during endoscopy,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Efficient detection of lesions during endoscopy,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:21.647047Z

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Observation e42c4dc0-43f7-4632-ba2b-857a298605b7 · outbound

This paper cites An image classification model based on transfer learning for ulcerative proctitis,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification An image classification model based on transfer learning for ulcerative proctitis,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:21.467911Z

Source-reported events for the cited work

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Observation 0ecb822c-149d-429e-82bd-5d28861dad30 · outbound

This paper cites Chollet, Xception: Deep learning with depthwise separable convolutions , 2017.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Chollet, Xception: Deep learning with depthwise separable convolutions , 2017

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:21.250587Z

Source-reported events for the cited work

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Observation b145121a-6e05-4275-873a-8109a1f27f23 · outbound

This paper cites an unresolved cited work.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Unresolved cited work

Reference 11

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Observation c82c515b-1de5-4e7d-a02e-a8ee5c0bb819 · outbound

This paper cites Huang, Z.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Huang, Z

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:20.852005Z

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Observation cdaeda93-e3bb-49af-9571-2fa8949e481d · outbound

This paper cites Diagnosis of ulcerative colitis from endoscopic images based on deep learning,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Diagnosis of ulcerative colitis from endoscopic images based on deep learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:20.627560Z

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Observation fc34d0fb-5175-4825-8769-24f670136d68 · outbound

This paper cites an unresolved cited work.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Unresolved cited work

Reference 14

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Observation 6d0ea268-8dc7-4493-8eca-5a53ab3296a4 · outbound

This paper cites Prototypical net- works for few-shot learning,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Prototypical net- works for few-shot learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:20.261863Z

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Observation c861122d-2062-4ac2-89d1-9897f80a7b61 · outbound

This paper cites an unresolved cited work.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Unresolved cited work

Reference 16

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Source-reported events for the cited work

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Observation 03de90e6-3f92-45f6-adf7-feea5f788499 · outbound

This paper cites Attention Is All You Need.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Attention Is All You Need

Reference 17

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Observation 6b182787-79de-4d47-b21e-add9f65777b3 · outbound

This paper cites BiFormer: Vision Transformer with Bi-Level Routing Attention.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification BiFormer: Vision Transformer with Bi-Level Routing Attention

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:19:19.157979Z

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Observation 4b5cef53-9f85-475a-97ab-2748add1e995 · outbound

This paper cites Kvasir: A multi-class image dataset for computer aided gas- trointestinal disease detection,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Kvasir: A multi-class image dataset for computer aided gas- trointestinal disease detection,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:20.003622Z

Source-reported events for the cited work

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Observation 0e48786e-e5f2-47ba-aca1-d5fb36fdee0b · outbound

This paper cites HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:19.862871Z

Source-reported events for the cited work

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Observation 97e5d83b-6511-4b27-93dd-3eb26d08c2d5 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin le- sions,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin le- sions,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:19.693198Z

Source-reported events for the cited work

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Observation 7e27120c-2096-41b4-ae2c-1d0ba42a814f · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 22

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Source-reported events for the cited work

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Observation 71e058fd-6ea8-4dfb-ad6a-684dd261397c · outbound

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Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Unresolved cited work

Reference 23

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 24262180-e464-489d-8395-75efcf5b9ccc · outbound

This paper cites ImageNet Large Scale Visual Recognition Challenge,.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification ImageNet Large Scale Visual Recognition Challenge,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:19:19.365276Z

Source-reported events for the cited work

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Observation 95466400-fb06-429a-b834-23774d99dec4 · outbound

This paper cites Meta-Learning with Fewer Tasks through Task Interpolation.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Meta-Learning with Fewer Tasks through Task Interpolation

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:19:18.827074Z

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Observation b78f4ca2-5710-4d59-b2a0-d06e2003900a · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification mixup: Beyond Empirical Risk Minimization

Reference 26

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Observation 9eda9cb4-b0c8-43a1-acbb-4c27c1ef6876 · outbound

This paper cites EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:19:18.991934Z

Source-reported events for the cited work

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Observation 6284a936-464a-44d1-b945-f89ad15f4d0f · outbound

This paper cites Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Reference 2017

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Observation 8a195702-f756-4f99-994d-9c3753aa767c · outbound

This paper cites Densely Connected Convolutional Networks.

Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification Densely Connected Convolutional Networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T12:19:17.266308Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.