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Paper Citation Record · LEDGER

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.16122.

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

pith.paper-citation-record.v1
2507.16122 v3

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:20:57.113187Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

35 of 35 outbound references displayed

  • verified exact1
  • verified fuzzy21
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8ddf4293-ae65-4c10-a6ee-83636a5e782d · outbound

This paper cites write newline.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:53.729003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:53.729003Z digest=sha256:126df1a1e89472af53f2c078ab811261029fb1729421cc10116d7c59ad5d4238

Observation 74a82b08-75df-461d-97a9-d6285474c40a · outbound

This paper cites In: International workshop on predictive intelligence in medicine.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: International workshop on predictive intelligence in medicine

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.423896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:53.824472Z digest=sha256:9106e1c462353d974c6906587f4e86083f2fb37c520b5ba400e3a21973568ece

Observation 10a68743-34a8-4127-83ae-a292da1473a0 · outbound

This paper cites an unresolved cited work.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:20:58.409870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:53.926982Z digest=sha256:852828eb21552c2af97bd5fa5b13374b7b63ddf093bce40aa9b15efe95a00867

Observation 795cbc64-3f7d-4ab4-8ec6-fc7b4bc4438f · outbound

This paper cites Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:54.030588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:54.030588Z digest=sha256:ec683e298515fbabb3e97156679de1b060ea1ee5327a868a7f37c864363d1be2

Observation e330641f-e638-4e7b-9064-dac462375d86 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:54.135402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:54.135402Z digest=sha256:136c708501c6ab218b20638b7d3ca031a330c6e8641756d8c275cb014b6a1dfb

Observation 36d2cb24-20fe-4aca-9953-b673a909b1d1 · outbound

This paper cites In: Medical Image Computing and Computer-Assisted Intervention--MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II 19.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Medical Image Computing and Computer-Assisted Intervention--MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II 19

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:54.250424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:54.250424Z digest=sha256:56336dd5cc7cf6f4b76531841d7b75dffa5df75a1a737860c5f16ba710a8d5f5

Observation 4bb94367-3dc1-4c21-8ea0-db8a3d6f2946 · outbound

This paper cites In: Proceedings of the IEEE International Conference on Computer Vision (ICCV).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE International Conference on Computer Vision (ICCV)

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.384141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:54.326400Z digest=sha256:45c9437c4a48bd187c0505d63b2a6511ec1445f5b2dc5eace29b0448340f40f6

Observation 07ab4a54-deca-4ee3-a032-a941ee4d80a9 · outbound

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

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:54.418436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:54.418436Z digest=sha256:6d6c338696770bc21fba32ac147a633ad82cfd9d344a7dbbc51b7b5218f2b2ff

Observation 00559246-1c94-423c-a7f4-57f42114c6bf · outbound

This paper cites In: International MICCAI brainlesion workshop.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: International MICCAI brainlesion workshop

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.369996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:54.495213Z digest=sha256:3246a5b4cc47d2b59d59225750e869bccabd82e271196c77e6b677a233b1d36a

Observation 4d0293cb-3e13-44fb-9be5-5fd50920a079 · outbound

This paper cites In: Proceedings of the IEEE/CVF winter conference on applications of computer vision.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE/CVF winter conference on applications of computer vision

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.356235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:54.596667Z digest=sha256:92db9d31aa9d8d0f87213898b7d420bfa08a03a3cbfac45b944cf56a21182769

Observation daa60448-c8dd-4acd-8d1a-32798b355235 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.341713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:54.709218Z digest=sha256:b0408f2254c75a02eca31da574dc8d9353f9422603c401d26140781dc0623c86

Observation 9881eecc-d4ab-40b4-a4c6-4749a4b869c9 · outbound

This paper cites an unresolved cited work.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Unresolved cited work

Reference 12

Resolution
verified exact
raw_fallback, observed 2026-08-06T15:20:58.010579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:54.927977Z digest=sha256:cdf726fb2cc9c9547f53e4ea51d0a296aec51bded6c57fd7e27f257e65770ba0

Observation 2735f231-fc37-4091-9aad-b58f794d02d4 · outbound

This paper cites IEEE transactions on medical imaging 42(5), 1484--1494 (2022).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation IEEE transactions on medical imaging 42(5), 1484--1494 (2022)

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.327403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.042231Z digest=sha256:dba6b5815940f31b1be57820ab916276aa1fed9325b3df261d667d7351e5e46b

Observation c1ee7fb6-62c1-4772-8bc5-7202b46822e2 · outbound

This paper cites In: Proc.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proc

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.312442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.126315Z digest=sha256:209cf7901b3c6b21a0620c0a1b9fafdf2744fca6218fe887594124599e882e1e

Observation a4258876-24c3-41ca-87ea-aa9a9898e134 · outbound

This paper cites Nature Methods 18(2), 203--211 (2021).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Nature Methods 18(2), 203--211 (2021)

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.298106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.217404Z digest=sha256:16177ac885f711348b763b8fbb4fd2433cfb4432709a2a6fe55732f70d6c8671

Observation cf22156a-6481-4d8b-8748-4431161d05b5 · outbound

This paper cites u r die Medizin 2019: Algorithmen--Systeme--Anwendungen. Proceedings des Workshops vom 17. bis 19. M \.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation u r die Medizin 2019: Algorithmen--Systeme--Anwendungen. Proceedings des Workshops vom 17. bis 19. M \

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.283287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.330630Z digest=sha256:03869d55011a3a44db62b9013c1ad2894a0234b1bba98e9bf9bc8de264e697a8

Observation 76c2bc79-2f5f-40c9-b29b-1364910b2743 · outbound

This paper cites Convolution-Free Medical Image Segmentation using Transformers.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Convolution-Free Medical Image Segmentation using Transformers

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T15:20:57.907808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.409569Z digest=sha256:5e81272b77acdde21970e8485cf8fe38baa9d46e97b6d8d7839530766171db9b

Observation a2a9be20-d714-4c06-a79f-feca8af73455 · outbound

This paper cites In: Proc.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proc

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.268246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.526737Z digest=sha256:b908c38cd45d8343f0deca63c55c44334a54ce202fad41deace8cb34b641b877

Observation 1453108f-149d-4f48-9ccb-f646f057f61a · outbound

This paper cites In: Fourth International Conference on 3D Vision (3DV).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Fourth International Conference on 3D Vision (3DV)

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.253227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.644165Z digest=sha256:dc8daddb915df47ed63d3d4d39dad0017d96d9e776c5c18488860671f610fde0

Observation ecc1abb1-ddf6-4786-a364-e4cc659c1ad5 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.238343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.719769Z digest=sha256:d1962f274844aea117fcd994287f89e48f8b09160ceaa48b8b280f587736b331

Observation ecd9da1d-9074-466d-8f43-db42fe02afaa · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.222198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.801454Z digest=sha256:687c0ddda37b0ff104fe13595b8fcae3f112dded5796c48faf471bfd724af4bd

Observation 80fa54c6-515e-456e-8927-72b0a91f4f75 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.206177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.890966Z digest=sha256:d2d46508d7d9d0bc83aee7576c680c58d1f9500f5ae27eee89d2ccdf95f8ddc5

Observation ff39db89-ac0a-4326-80b4-a55c84482ba7 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.190640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:55.975183Z digest=sha256:e46b24753aee97c2342c67e4c7d9f65291e203c6a62f820a3291377af1709e24

Observation a9fdd3f7-b494-4b19-a581-eee0ac9b6f7d · outbound

This paper cites Bounds on the number of maximal subgroups of finite groups.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Bounds on the number of maximal subgroups of finite groups

Reference 24

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T15:20:57.862548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.087092Z digest=sha256:1ca6270d0bea4738f597e6609adc546402d7bea081c3cdae182491123c88b36f

Observation cdd34444-adf6-4d68-83ac-9d6b728bbd6b · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018)

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.175201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.195573Z digest=sha256:a5b0304ce217472a3a7f782c321d457e0489c17d33419dfcf382f636cad38d58

Observation 079d1389-3a4b-4256-bd0d-2f3e9414848c · outbound

This paper cites IEEE Transactions on Medical Imaging (2024).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation IEEE Transactions on Medical Imaging (2024)

Reference 26

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T15:20:57.546160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.279555Z digest=sha256:5e4d0ed25f855224754dfa00c8bb3f8a036263edf106c40c3011d1488b0de0d5

Observation 3645f327-8f75-4d2c-b1e1-568efd0646a6 · outbound

This paper cites arXiv e-prints pp.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation arXiv e-prints pp

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.160173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.374672Z digest=sha256:b41b01954aedf48152b58c22c3666c05290b93d47e4126416964b5ef373f6185

Observation a3a4f4fc-8fb9-4876-b80d-8e583204d891 · outbound

This paper cites Medical Image Analysis 73, 102222 (2022).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Medical Image Analysis 73, 102222 (2022)

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.143643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.455068Z digest=sha256:3d5ccfa01d7ffbd0f9ab06edfbdeb2ddf004595d4b9d892b5b3528872c1a07b3

Observation 6ddddb1b-34e5-4c60-ad62-54e652252a40 · outbound

This paper cites In: Proceedings of the European conference on computer vision (ECCV).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the European conference on computer vision (ECCV)

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:56.557520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:56.557520Z digest=sha256:da7175b83d4dd0056802ab00613d814e51ba45a3761ec1e63c68eb11bb615669

Observation e64b2b86-6070-4277-98d8-289e5f497eea · outbound

This paper cites CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:56.666168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:56.666168Z digest=sha256:0d40818a3a2c01525a718cb0576a0e34f2791455069d0b98924ee67a6b5ba61f

Observation 1b23dd67-30dc-4961-a42f-a2a48decd277 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.116440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.769975Z digest=sha256:230073f4eec756433dfd202faae4f3cbdcd5fdebd9524da3ff957ba2ec0cf822

Observation 30a96da9-7b29-4b77-9b3f-56a83f4830c5 · outbound

This paper cites IEEE transactions on image processing 32, 4036--4045 (2023).

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation IEEE transactions on image processing 32, 4036--4045 (2023)

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.100309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:56.853482Z digest=sha256:81c180a3582d0a3fe8c9c6513d036f79578ae8911cbfda686c34192e3993c1c0

Observation 4f856173-11dd-4d76-9b8c-39a279eeae79 · outbound

This paper cites nnFormer: Interleaved Transformer for Volumetric Segmentation.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation nnFormer: Interleaved Transformer for Volumetric Segmentation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:56.965523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:56.965523Z digest=sha256:737270c264cf3f29d1149388deb3e751b35f0acfff3c8c82cbc63b192f08a4ac

Observation 89c8bd66-43e5-4fc9-85e5-c15e23d5ab69 · outbound

This paper cites In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:58.084962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T15:20:57.085441Z digest=sha256:24bdeb80b38790f684ff33ac67824196945b01babcdc19e46bec2d83c86b5980

Observation 3da7961e-c67c-424a-93ee-6e2d69c7bb0d · outbound

This paper cites Cbam: Convolutional block attention module.

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation Cbam: Convolutional block attention module

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:57.113187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:20:57.113187Z digest=sha256:45c9b0835156bf6a601b788bbd39a197f4cf03e818f18487f7c0b7288e09b11c

Pith citing papers

No inbound Pith citation observations are available.