M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation | Paper Citation Record

Observation 166e9164-e3fb-461b-94b8-c4c040b91fe9 · outbound

This paper cites Reducing seg- mentation failures in cardiac mri via late feature fusion and gan-based augmentation.Computers in Biology and Medicine, 161:106973.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Reducing seg- mentation failures in cardiac mri via late feature fusion and gan-based augmentation.Computers in Biology and Medicine, 161:106973

Reference 1

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Observation 91fb216f-b2ea-409e-a1d7-d425a23d1921 · outbound

This paper cites Dynamic weighted knowledge distilla- tion for brain tumor segmentation.Pattern Recognition, 155: 110731.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Dynamic weighted knowledge distilla- tion for brain tumor segmentation.Pattern Recognition, 155: 110731

Reference 2

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Observation ffc73129-a123-4a1e-b115-1abe4ac5d24e · outbound

This paper cites An overview of load balancing in hetnets: Old myths and open problems.IEEE Wireless Communications, 21(2):18–25.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation An overview of load balancing in hetnets: Old myths and open problems.IEEE Wireless Communications, 21(2):18–25

Reference 3

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Observation a54f2b96-43c4-4b01-b378-c34c9088f327 · outbound

This paper cites Lcmf-net: A lightweight collaborative multimodal fusion network for brain tumor segmentation.Neural Networks, page 108257.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Lcmf-net: A lightweight collaborative multimodal fusion network for brain tumor segmentation.Neural Networks, page 108257

Reference 4

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Observation 0f558cbd-2fdc-49e3-a453-5b3102e46e9f · outbound

This paper cites Moe-lightning: High-throughput moe inference on memory-constrained gpus.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Moe-lightning: High-throughput moe inference on memory-constrained gpus

Reference 5

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Observation ac7a34b1-9514-4728-b6d7-67a53ffe0e54 · outbound

This paper cites Lienkamp, Thomas Brox, and Olaf Ronneberger.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Lienkamp, Thomas Brox, and Olaf Ronneberger

Reference 6

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Observation f452dbe2-1903-4c8f-86f7-f9daaae7d46d · outbound

This paper cites Denseformer-moe: A dense transformer foundation model with mixture of experts for multi-task brain image analysis.IEEE Transactions on Medical Imaging.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Denseformer-moe: A dense transformer foundation model with mixture of experts for multi-task brain image analysis.IEEE Transactions on Medical Imaging

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.310391Z

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Observation 7041fd73-cea6-4eb4-89d9-e8c04db46b48 · outbound

This paper cites Decoupling feature-driven and mul- timodal fusion attention for clothing-changing person re- identification.Artificial Intelligence Review, 58(8):241.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Decoupling feature-driven and mul- timodal fusion attention for clothing-changing person re- identification.Artificial Intelligence Review, 58(8):241

Reference 8

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Observation 7897a74e-8a04-4160-b3b0-ed2d52e8522a · outbound

This paper cites Maximum score rout- ing for mixture-of-experts.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Maximum score rout- ing for mixture-of-experts

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.317556Z

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Observation 1799bc3e-290c-45a8-aaaa-731f45d24fe9 · outbound

This paper cites Mixture-of-experts for semantic segmentation of re- moting sensing image.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Mixture-of-experts for semantic segmentation of re- moting sensing image

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.303328Z

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Observation cbba14df-b31c-4e24-85d3-4ac272011772 · outbound

This paper cites Swinunetr-v2: Stronger swin transformers with stagewise convolutions for 3d medi- cal image segmentation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Swinunetr-v2: Stronger swin transformers with stagewise convolutions for 3d medi- cal image segmentation

Reference 11

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Observation 4e7c52c2-11ff-4771-8cdc-8994905a45a9 · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmen- tation.Nature methods, 18(2):203–211.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmen- tation.Nature methods, 18(2):203–211

Reference 12

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Observation 1e3d1985-c309-4d7c-beaa-00b1d5fb3da8 · outbound

This paper cites an unresolved cited work.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-05-26T04:21:42.332751Z

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Observation 70ebd2b1-30e1-4631-9e71-79f644b29fc5 · outbound

This paper cites THOR-MoE: Hierarchical task-guided and context-responsive routing for neural machine translation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation THOR-MoE: Hierarchical task-guided and context-responsive routing for neural machine translation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.210119Z

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Observation 3ff67c1c-1800-4048-b27a-ed3935b944ee · outbound

This paper cites LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:15:39.153725Z

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Observation d76adff2-2b69-40e5-ac28-5ed8fc424bb2 · outbound

This paper cites Multimodal brain tumor segmen- tation boosted by monomodal normal brain images.IEEE Transactions on Image Processing, 33:1199–1210.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Multimodal brain tumor segmen- tation boosted by monomodal normal brain images.IEEE Transactions on Image Processing, 33:1199–1210

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.322110Z

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Observation 36105a97-a720-4518-b27c-c666b3097dfd · outbound

This paper cites Cswin-unet: Transformer unet with cross-shaped windows for medical image segmentation.Information Fusion, 113: 102634.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Cswin-unet: Transformer unet with cross-shaped windows for medical image segmentation.Information Fusion, 113: 102634

Reference 17

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Observation 92ca083f-66cf-4bfd-99a5-518a33924136 · outbound

This paper cites Paddleseg: A high-efficient development toolkit for image segmentation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Paddleseg: A high-efficient development toolkit for image segmentation

Reference 18

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Observation 2acb779f-afe6-4542-88eb-a56f0bd34ee2 · outbound

This paper cites 3d mri brain tumor segmentation using autoencoder regularization.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation 3d mri brain tumor segmentation using autoencoder regularization

Reference 19

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Observation dd70ca9d-9d32-491c-84eb-156850f93728 · outbound

This paper cites an unresolved cited work.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Unresolved cited work

Reference 20

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Observation a5010780-a202-480e-94eb-8a57d4b68dc4 · outbound

This paper cites Vcanet: Vision transformer with fusion channel and spatial attention module for 3d brain tu- mor segmentation.Computers in Biology and Medicine, 186: 109662.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Vcanet: Vision transformer with fusion channel and spatial attention module for 3d brain tu- mor segmentation.Computers in Biology and Medicine, 186: 109662

Reference 21

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Observation 35450e3f-aabc-4efb-997d-e6008263d531 · outbound

This paper cites A review of affective computing: From unimodal anal- ysis to multimodal fusion.Information fusion, 37:98–125.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation A review of affective computing: From unimodal anal- ysis to multimodal fusion.Information fusion, 37:98–125

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.190430Z

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Observation 1aebadeb-bc43-42d3-baa1-81cdaf5f721a · outbound

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M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Unresolved cited work

Reference 23

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Observation 9a1b4653-31e8-4161-8c93-c4bad14aa03a · outbound

This paper cites A critical review on segmentation of glioma brain tumor and prediction of 9 overall survival.Archives of Computational Methods in En- gineering, 32(3):1525–1569.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation A critical review on segmentation of glioma brain tumor and prediction of 9 overall survival.Archives of Computational Methods in En- gineering, 32(3):1525–1569

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Observation a8b45c39-9d25-4493-a320-ae6eb0e53737 · outbound

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

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation U- net: Convolutional networks for biomedical image segmen- tation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.214201Z

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Observation 3c27023b-9876-4a83-b441-89abc4cfde83 · outbound

This paper cites Johansen, Dag Johansen, Michael A.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Johansen, Dag Johansen, Michael A

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.336304Z

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Observation bd36b2e8-2d0a-493a-8581-2ac3da5c5035 · outbound

This paper cites an unresolved cited work.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-05-26T04:21:42.272869Z

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Observation 1df3e5cb-13f8-4570-83dc-b2f6cfde17a2 · outbound

This paper cites Narrowing the semantic gaps in u-net with learnable skip connections: The case of medical image segmentation.Neu- ral Networks, 178:106546.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Narrowing the semantic gaps in u-net with learnable skip connections: The case of medical image segmentation.Neu- ral Networks, 178:106546

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.314027Z

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Observation 991513e3-1f98-4276-816c-67754c824b5a · outbound

This paper cites Mff-sdd: A bidirectional guidance and multiscale multimodal fusion model for small defect detection in industrial films.IEEE Transactions on Industrial Informatics.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Mff-sdd: A bidirectional guidance and multiscale multimodal fusion model for small defect detection in industrial films.IEEE Transactions on Industrial Informatics

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Observation 57a21cb7-3d72-4188-a791-b0342bebc54b · outbound

This paper cites Transbts: Multimodal brain tumor segmen- tation using transformer.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Transbts: Multimodal brain tumor segmen- tation using transformer

Reference 30

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Observation 35c2b62b-2a8e-4b8f-b048-0bfe7cb8b224 · outbound

This paper cites Deep multimodal fusion by chan- nel exchanging.Advances in neural information processing systems, 33:4835–4845.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Deep multimodal fusion by chan- nel exchanging.Advances in neural information processing systems, 33:4835–4845

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.295876Z

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Observation 4aa00c20-81fa-4c52-9bdf-2ddd78b6199a · outbound

This paper cites Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation

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Observation 2c3efdd0-705d-469a-9c7f-23ce52c3017c · outbound

This paper cites Lightweight real-time semantic seg- mentation network with efficient transformer and cnn.IEEE Transactions on Intelligent Transportation Systems, 24(12): 15897–15906.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Lightweight real-time semantic seg- mentation network with efficient transformer and cnn.IEEE Transactions on Intelligent Transportation Systems, 24(12): 15897–15906

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Observation 2ae1712e-53b6-48af-bacc-1b40d60695e9 · outbound

This paper cites Dynamic multimodal fu- sion.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Dynamic multimodal fu- sion

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Observation 506f595b-e0c6-4a1c-b779-05f0f68b5127 · outbound

This paper cites XMoE: Sparse models with fine-grained and adaptive expert selection.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation XMoE: Sparse models with fine-grained and adaptive expert selection

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.329471Z

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Observation 586d6d80-e615-4f32-af4a-3c77b466f647 · outbound

This paper cites All- in-one medical image restoration via task-adaptive routing.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation All- in-one medical image restoration via task-adaptive routing

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.277028Z

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Observation b826c4f1-7a98-4104-aa1c-2b11700c82d4 · outbound

This paper cites Su- perlightnet: Lightweight parameter aggregation network for multimodal brain tumor segmentation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Su- perlightnet: Lightweight parameter aggregation network for multimodal brain tumor segmentation

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.257193Z

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Observation 00aff0eb-dcc1-449b-a63e-57c0ef047ebf · outbound

This paper cites Resilient datacenter load balancing in the wild.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Resilient datacenter load balancing in the wild

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.269085Z

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Observation 111c5751-ba8e-49a3-aa3a-032a6a2cd01f · outbound

This paper cites Sed: Searching enhanced decoder with switchable skip connection for semantic segmentation.Pat- tern Recognition, 149:110196.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Sed: Searching enhanced decoder with switchable skip connection for semantic segmentation.Pat- tern Recognition, 149:110196

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.243927Z

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Observation 857d8b5e-56b4-4f6c-b399-20a61586ad79 · outbound

This paper cites Mpmoe: Memory efficient moe for pre-trained models with adaptive pipeline parallelism.IEEE Transactions on Parallel and Distributed Systems, 35(6):998–1011.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Mpmoe: Memory efficient moe for pre-trained models with adaptive pipeline parallelism.IEEE Transactions on Parallel and Distributed Systems, 35(6):998–1011

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.261509Z

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Observation 8b78bc7b-ff5b-4320-97bf-14b1ecb891c6 · outbound

This paper cites Contrast-aware hybrid attention network for medi- cal image segmentation.Information Sciences, page 123000.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Contrast-aware hybrid attention network for medi- cal image segmentation.Information Sciences, page 123000

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.281198Z

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Observation bc0f2841-6c66-4f00-b6ca-4b1bf0a67004 · outbound

This paper cites Dcl-se: Dynamic curricu- lum learning for spatiotemporal encoding of brain imaging.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Dcl-se: Dynamic curricu- lum learning for spatiotemporal encoding of brain imaging

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Resolution: verified exact; arxiv_id, observed 2026-05-09T06:15:39.148842Z

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Observation 3a42bc57-2e2b-406d-a548-844ed0a20a7f · outbound

This paper cites Damnet: Dynamic mobile architectures for alzheimer’s disease.Computers in Biology and Medicine, 185:109517.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Damnet: Dynamic mobile architectures for alzheimer’s disease.Computers in Biology and Medicine, 185:109517

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.240338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b3ded3fd-2320-4491-94a3-2e15338c70f6 · outbound

This paper cites High-resolution encoder–decoder networks for low-contrast medical image segmentation.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation High-resolution encoder–decoder networks for low-contrast medical image segmentation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.233337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d40da06e-7c71-4a96-ac9e-653b90ab2820 · outbound

This paper cites M2gcnet: Multi-modal graph convolution network for precise brain tumor segmentation across multi- ple mri sequences.IEEE Transactions on Image Processing.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation M2gcnet: Multi-modal graph convolution network for precise brain tumor segmentation across multi- ple mri sequences.IEEE Transactions on Image Processing

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.340285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ca0243da-ce9d-4f7a-80ee-ad70656f1746 · outbound

This paper cites An efficient secure and adaptive routing protocol based on gmm- hmm-lstm for internet of underwater things.IEEE Internet of Things Journal, 11(9):16491–16504.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation An efficient secure and adaptive routing protocol based on gmm- hmm-lstm for internet of underwater things.IEEE Internet of Things Journal, 11(9):16491–16504

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.299691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c70a5a9d-08f8-4ccf-b1c2-358ed7a2b65b · outbound

This paper cites Brain tumor segmentation in mri with multi-modality spatial information enhancement and bound- ary shape correction.Pattern Recognition, 153:110553.

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation Brain tumor segmentation in mri with multi-modality spatial information enhancement and bound- ary shape correction.Pattern Recognition, 153:110553

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T04:21:42.221962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Pith citing papers