Paper Citation Record · LEDGER

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder

As of 22 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2412.06262.

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

pith.paper-citation-record.v1
2412.06262 v1

Coverage vector

measured 29 of 29 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-11T19:55:53.935074Z

measured 29 of 29 standing notices

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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

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Outbound references

Observation f50e35c6-b642-4a22-bd6d-48e0696ab74d · outbound

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

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Observation 1b6dfd0f-436a-49f6-8b59-9c8d574b6f25 · outbound

This paper cites Deep residual learning for image recog- nition,.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Deep residual learning for image recog- nition,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.341262Z

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Observation 331729c7-0163-4964-b15b-fccdae1b0834 · outbound

This paper cites Neue methoden zur approxi- mativen integration der differentialgleichungen einer un- abh¨angigen ver ¨anderlichen.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Neue methoden zur approxi- mativen integration der differentialgleichungen einer un- abh¨angigen ver ¨anderlichen

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.304753Z

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Observation 531d20a7-7bee-4bbe-bfd2-ac0f1c06d4ff · outbound

This paper cites [Liu et al., 2021] Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder [Liu et al., 2021] Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo

Reference 12

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Observation 5eaa526f-9c2d-4275-9502-ca5b88c39c60 · outbound

This paper cites At- tention u-net: Learning where to look for the pancreas,.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder At- tention u-net: Learning where to look for the pancreas,

Reference 15

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Observation 80dd5436-f1bc-439a-96da-b7296f54c628 · outbound

This paper cites Attractors in memory.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Attractors in memory

Reference 16

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Observation db8f6d80-0a5d-4e05-abe9-84ce2369b084 · outbound

This paper cites Malunet: A multi-attention and light-weight unet for skin lesion segmentation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Malunet: A multi-attention and light-weight unet for skin lesion segmentation

Reference 18

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Observation 5a7fe2aa-728f-4aac-8e4a-00407ab5b4f6 · outbound

This paper cites EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation

Reference 19

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Observation 782f88c1-5c0e-4ead-b675-745bdf05754b · outbound

This paper cites Mlp-mixer: An all-mlp architecture for vision.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Mlp-mixer: An all-mlp architecture for vision

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.180350Z

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Observation d6f36558-95f2-4231-a28e-0e3869b2547b · outbound

This paper cites nmode-unet: A novel network for semantic segmentation of medical images.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder nmode-unet: A novel network for semantic segmentation of medical images

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.147641Z

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Observation e701b1ea-61ef-4bb9-be20-8da1baf4f239 · outbound

This paper cites Wills, Colin Lever, Francesca Cacucci, Neil Burgess, and John O’Keefe.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Wills, Colin Lever, Francesca Cacucci, Neil Burgess, and John O’Keefe

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.119577Z

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Observation 49fc3951-b547-427e-9f8d-d1c1f2f131b7 · outbound

This paper cites Fat-net: Fea- ture adaptive transformers for automated skin lesion seg- mentation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Fat-net: Fea- ture adaptive transformers for automated skin lesion seg- mentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.101665Z

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Observation 39a526dd-51d2-4224-96a4-fb5e671841a3 · outbound

This paper cites nmode: neural memory ordinary differ- ential equation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder nmode: neural memory ordinary differ- ential equation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.085435Z

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Observation e4405b6a-212a-474b-a5ba-1ef45710aedf · outbound

This paper cites Road extraction by deep residual u-net.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Road extraction by deep residual u-net

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.070627Z

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Observation cac82d45-5b6a-4025-936c-c140cbc5cef3 · outbound

This paper cites Transfuse: Fusing transformers and cnns for med- ical image segmentation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Transfuse: Fusing transformers and cnns for med- ical image segmentation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.057361Z

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Observation 5b4056a4-8e47-4cd6-8dbd-5bc4a76678d8 · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmenta- tion, 2018.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Unet++: A nested u-net architecture for medical image segmenta- tion, 2018

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.041016Z

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Observation f68e0337-9e8a-4069-a292-243e968f3961 · outbound

This paper cites A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 1845

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Observation 426ef595-d29e-4208-98dc-9d81aa62676d · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Swin-unet: Unet-like pure transformer for medical image segmentation

Reference 1883

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.416938Z

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Observation 6f2d00eb-8710-4af0-b383-2ea4b9b25403 · outbound

This paper cites Enhancing robustness of medical image segmentation model with neural memory ordinary differ- ential equation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Enhancing robustness of medical image segmentation model with neural memory ordinary differ- ential equation

Reference 1900

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.285848Z

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Observation 76edfcec-66c6-4a77-98c6-b954f569899f · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder U-net: Convolutional networks for biomedical image segmentation

Reference 2005

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Observation d511c9ea-d18f-4441-b535-08f785080d50 · outbound

This paper cites Med- ical image segmentation using discretized nmode.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Med- ical image segmentation using discretized nmode

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.321827Z

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Observation a0c9c8e2-653a-4b43-95b7-e5bd9f58c55a · outbound

This paper cites Decoupled Weight Decay Regularization.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Decoupled Weight Decay Regularization

Reference 2016

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Observation a6c66bd0-38b4-46b4-8a51-8c3ca7f3ea47 · outbound

This paper cites Separable self-attention for mobile vision trans- formers,.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Separable self-attention for mobile vision trans- formers,

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.256822Z

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Observation 83ef6c7d-422b-41f4-81ab-6cdb1014fbbc · outbound

This paper cites Segnetr: Rethinking the local-global interactions and skip connections in u-shaped networks,.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Segnetr: Rethinking the local-global interactions and skip connections in u-shaped networks,

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.390559Z

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Observation 7bc23756-efc9-4014-981e-f614f28a7ede · outbound

This paper cites Augmented neural odes,.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Augmented neural odes,

Reference 2020

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Observation 662789d0-ec0a-4e48-a2cb-721d33b4720e · outbound

This paper cites Unext: Mlp-based rapid medical im- age segmentation network.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Unext: Mlp-based rapid medical im- age segmentation network

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.162339Z

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Observation fd23a40f-ee7d-4a52-918a-819800d9d7ac · outbound

This paper cites Neural ordinary dif- ferential equations.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Neural ordinary dif- ferential equations

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.403236Z

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Observation b65f2d10-b89f-40d0-8615-938de155910f · outbound

This paper cites nmpls-net: Segmenting pulmonary lobes us- ing nmode.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder nmpls-net: Segmenting pulmonary lobes us- ing nmode

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.375683Z

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Observation 06522f5c-1dbc-4198-add4-584256aa6d71 · outbound

This paper cites Kevin Zhou, and Shuguang Cui.

A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder Kevin Zhou, and Shuguang Cui

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:55:54.134667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

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