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Paper Citation Record · LEDGER

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2505.24481.

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

pith.paper-citation-record.v1
2505.24481 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:25:17.679819Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

45 of 45 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 274f9ddb-79e7-42dd-9409-00b00fe3d37e · outbound

This paper cites Ronneberger, P.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Ronneberger, P

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:14.469614Z digest=sha256:e3ad58848bf8575a3edf8193100e730341043005b2eef8d220cac69c137ddcdf

Observation 0b550f6d-31e8-4bff-af6d-c64bc683c120 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:14.528066Z digest=sha256:6a0af9c498374ea2651c8839c035f6df8031f4255183f73a6b86d0e442405b54

Observation bab99f09-b223-436d-84a1-28d7a8b196cc · outbound

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

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 3

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source=pdf_text observed=2026-08-07T12:25:14.578369Z digest=sha256:49aed61d95bfeddf48bd32f9eb769109be58edf4d8376f29722fe9b26a830936

Observation e8b1d665-0fdf-4595-9c74-f72050ce9bbb · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 4

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:14.637331Z digest=sha256:7dd8d5a0b48ff2a7391093f08dacf0a2becdbde11a43abaeed427daa695c9e2d

Observation 25096845-5727-4817-a0e2-0d89bd2c4bf4 · outbound

This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 5

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source=pdf_text observed=2026-08-07T12:25:14.722093Z digest=sha256:8693ffb71edac85faa35eb4358e1787d75483e1efad5f34257630a7840667943

Observation bb9099c3-5c89-4600-b1e6-ce84c28bbfd3 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:14.785663Z digest=sha256:cce85a8e866c4ff8c3f5d58f731c45694fc10e0835fb14b52e624ab6b6047856

Observation 056bd696-acd2-471e-85a2-a99249626920 · outbound

This paper cites Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

Reference 7

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source=pdf_text observed=2026-08-07T12:25:14.869114Z digest=sha256:7804355c5a07ad1a15a42370e3610d137d58f38bb494606727cbcf428113768e

Observation 41ee9c82-9f6f-4312-9b7f-b6dd1be313bc · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 8

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:14.932015Z digest=sha256:9d0e8c49df1292aca88a7a32f19d95bc35d85f96712a287c17c5a11f4d702efb

Observation 469cd7f7-55e6-415c-9474-ca0d1d08678b · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:15.019549Z digest=sha256:de7e01a64d8c175e388f2c5c4eaffe2942c43a2bb6be56f728d2154173829826

Observation ad55f86f-95e9-49b0-9c9a-3bc723e453ba · outbound

This paper cites IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design

Reference 10

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source=pdf_text observed=2026-08-07T12:25:15.123872Z digest=sha256:3623124175da14498dd57dcf2ee67f88c27115111c537f233df01b4a75843bd1

Observation 3f790a3f-0da6-4c86-8c2a-7f5d5a4eb967 · outbound

This paper cites Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model

Reference 11

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source=pdf_text observed=2026-08-07T12:25:15.204023Z digest=sha256:5b00068b660af2ea32372b115acf001c73877a062a53546fcd4178e9d0508359

Observation d37eafb2-3d1c-43b8-a19c-5bb27f7f38dc · outbound

This paper cites Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Reference 12

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source=pdf_text observed=2026-08-07T12:25:15.301678Z digest=sha256:24c717a1f8092afb3774a73ba1680e69f13fb7ed733765d0bd7553a64381f33a

Observation e347409f-efc4-46d7-9fb8-304d5535cb34 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:15.439462Z digest=sha256:ae5ac10a5e916e5ae7bccee58b7c53e750d8ce5ba413141ac4fa741668ba2c15

Observation 1f44533b-4808-4c09-b9c0-c177b58b0e34 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 14

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source=pdf_text observed=2026-08-07T12:25:15.520827Z digest=sha256:c42abb49b034f6e4bd4e812cc5af37984c102c0f5147ca4887ee1601fa6d66b5

Observation 0edd142a-6419-46a5-8ec9-4da32c618a67 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:15.563300Z digest=sha256:751efcceaa99d6a44c1305dd020dd33acefe210385b9aeea33e6af2b5ac9f7c6

Observation 6edb8321-b2ea-4967-a448-07f85f88a12c · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:15.604019Z digest=sha256:c5e32d9cc8ab22fb0ec2598d46220276faf144c239308dc89f65fbec87ea7382

Observation c485b61d-f541-4341-868d-4becf6a447e1 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 17

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source=pdf_text observed=2026-08-07T12:25:15.630520Z digest=sha256:a6d284740227cd3f23b6dcaf2c4712b4a60b71919eededd5f0bc1185ae7c3d76

Observation e2a35acb-f46b-4585-bc7a-df8abd61ae76 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:15.708548Z digest=sha256:5f8bc48b96caccc0672d388feb4512d5dff12af985b36bfe247a34a3444c356d

Observation 85488e2f-0a27-4f40-915d-2995c2b08bf9 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:15.789834Z digest=sha256:a3b5ebd5cb0246143ea09dc616d636fdf8defab1d8ce9f53ee277ba7b459eda1

Observation 3a531c97-b223-4cd4-9cdf-e2d681bb1c73 · outbound

This paper cites MixConv: Mixed Depthwise Convolutional Kernels.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation MixConv: Mixed Depthwise Convolutional Kernels

Reference 20

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source=pdf_text observed=2026-08-07T12:25:15.883710Z digest=sha256:a4364dd4a2f2c880ebac57bae5ab40a59970f5547399a3d2e349da50080700bc

Observation 3089e0d3-94b8-4307-9ff5-561370deba78 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:15.988031Z digest=sha256:4f37010d78451e650ed6560479fb8b7d0949f3d210bf9c754709a9f22f29f6fc

Observation 02743b31-08a7-4697-a8b2-04a8a3a980c3 · outbound

This paper cites Vaswani, N.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Vaswani, N

Reference 22

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source=pdf_text observed=2026-08-07T12:25:16.076033Z digest=sha256:9a6c13568828433e56b4e061b84d779cea3091142646c0ca68096a47425ba23d

Observation dbc8c21c-bc77-4329-89ad-1ee50e5476fd · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 23

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source=pdf_text observed=2026-08-07T12:25:16.182800Z digest=sha256:77527bb30cbf91cb3683af85ac1169f65f81012a6b064c6223654581ef3211d4

Observation 69a6c6f0-b713-453e-a80d-72b38072efea · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-07T12:25:16.268510Z digest=sha256:d129ceaf56244b41d388275eb13a76c0fd92459ddffb28049d2f9c3e5a2bdd5d

Observation e08d60b8-02a1-4773-9755-6e54d8731325 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:16.344180Z digest=sha256:721673349b47fd306b3c9a2ce60edc11c136e9b13615a3e9c62eb5a26d2eed1a

Observation 2ee5e4c0-3845-422a-a4ec-31abf346bd55 · outbound

This paper cites TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation

Reference 26

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local_arxiv, observed 2026-08-07T12:25:17.891708Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:16.416926Z digest=sha256:605ac5ed668a480095a339db4b0ca84952cdceecc124e867c336005c7ec19cdb

Observation 7aa8a871-412a-4633-abba-ed4ecbb5844f · outbound

This paper cites HC-Mamba: Vision MAMBA with Hybrid Convolutional Techniques for Medical Image Segmentation.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation HC-Mamba: Vision MAMBA with Hybrid Convolutional Techniques for Medical Image Segmentation

Reference 27

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source=pdf_text observed=2026-08-07T12:25:16.500116Z digest=sha256:58f290dc9de383543f6ce3ae8f554d9403dcb5b07c754b03fdef5ac4d05fb5e8

Observation 6acbaca1-3748-4e60-866f-fd4cb420be25 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-07T12:25:16.569355Z digest=sha256:93ad0f15280197125d7c5f3c97be60d15e7cae35daf028382a2b9f05856cc976

Observation 6e3f0b73-e771-4984-8fde-91beff12126f · outbound

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

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 29

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source=pdf_text observed=2026-08-07T12:25:16.640745Z digest=sha256:3b21a4b34219a9f8669afbbe251c4b910812a1acd3b1e481b0968c2e841d84bb

Observation 71ad64ee-4d0a-41d5-afd4-e3c3e5190d13 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Efficiently Modeling Long Sequences with Structured State Spaces

Reference 30

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source=pdf_text observed=2026-08-07T12:25:16.741078Z digest=sha256:bb3b4da2d0753efa0103702d000afa0413dd44e1a9d5b4add2346fbf710c4766

Observation b23be43a-d229-4763-8e00-ec90826594fa · outbound

This paper cites On the Parameterization and Initialization of Diagonal State Space Models.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation On the Parameterization and Initialization of Diagonal State Space Models

Reference 31

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source=pdf_text observed=2026-08-07T12:25:16.824887Z digest=sha256:17b3ef8a6d34603452989fd1645872b65b55685a29e8918f0a1eab00b2e992e8

Observation 348dc76c-bbdd-4fda-8e99-4ddd8fbd43e4 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 32

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source=pdf_text observed=2026-08-07T12:25:16.899177Z digest=sha256:1c43ed1f2daf0ed693da641429faa4e793718738fe6558a83bab397675727a3c

Observation b4627dc6-9496-42b7-ae39-2064105221d6 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:16.974621Z digest=sha256:a054b32d5e521a00280c4bbcd6bfed5343514e49cf26c5566d99cc42035894f1

Observation 3628e01a-c42c-489d-b7d8-033e9a507fa8 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:17.045968Z digest=sha256:41edfc438359174f9e9d06a267bcd8b103406b13722805a3c50f94ada5750c45

Observation ca9c76b4-e341-43a0-b0f4-8b36335dc639 · outbound

This paper cites Landman, Z.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Landman, Z

Reference 35

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raw_fallback, observed 2026-08-07T12:25:20.035709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.129087Z digest=sha256:6b3ee16b92b5282187a5bdf2cfe6a85f6a20469a758e8866c63175af33f98d86

Observation 09316075-908b-45a5-b180-ee399a568127 · outbound

This paper cites Bernard, A.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Bernard, A

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T12:25:19.807145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.200015Z digest=sha256:018f44b44de790e18e6809661dbfe59867a4c0807c43ec953bdb4817f92466ab

Observation 1fe7c3a0-7c79-4642-b55e-a1b31d264515 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:19.530108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d915c273-fa17-4880-809d-a9bdbbc3a0b3 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:19.300621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.375261Z digest=sha256:6a00aaeb9c156743d2b5fa867db3822bd9a503467f10c299c0ef7d4cde795f4f

Observation a9e5e77f-407f-472e-9bbb-d78e9d3d7d7d · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:19.110234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.423853Z digest=sha256:5ae35ebd96abc364bfb82dd8cc999bfd0b8ba9db68ade4c0cb63182c6567f20c

Observation 5cbe8df8-be18-4fe4-8c7d-40270165a402 · outbound

This paper cites ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:25:17.480628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:25:17.480628Z digest=sha256:fbc48a83a144d7e3b8d8aa525a67ab78dcc6ac4338e61134dc396b485920c313

Observation 84023f98-31e3-40ac-a439-ed918cdf59a3 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:18.886862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.525361Z digest=sha256:cb5ad79286d6a80dbbbd0a640e9cee8092bebec75d153e3455680ab951c99afe

Observation d8027a29-0b07-448e-a31c-f56d6e17be6b · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:18.664803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.557532Z digest=sha256:62c6d237bcc16fde9e40639f5971942252b75cb671f46750a1632583bc58e05f

Observation d7637518-439a-4760-b75a-63b8b67b8b95 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:18.531633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.593159Z digest=sha256:05a50c8dd4d203761e92274c8ca70147cafc03796e3b76525161747697bc2b29

Observation 642260d5-7d0b-49d7-a638-0e168dd12da7 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:18.355615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.646087Z digest=sha256:8fd60a2e49c253a09d3e86dcf8a9de02ae8f32353fdeb105ed3358b36e876706

Observation 00fa8a1c-c748-40ec-863c-7d64179249a1 · outbound

This paper cites an unresolved cited work.

ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:25:18.161258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:25:17.679819Z digest=sha256:b5826d70a4abc7df4d6afb6c0cdf79587832d9c945169b53b52369b2ac73b50e

Pith citing papers

No inbound Pith citation observations are available.