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Paper Citation Record · LEDGER

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder

As of 15 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 1 inbound Pith citation observation for arXiv:2412.07804.

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

pith.paper-citation-record.v1
2412.07804 v3

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:51:18.302513Z

measured 21 of 21 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:51:18.229616Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-11T19:51:18.368209Z

Reference resolution

20 of 20 outbound references displayed

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Outbound references

Observation a09b84b5-0aa9-4188-ad1d-a6b178cb8778 · outbound

This paper cites Within this category, diffuse gliomas are the most frequently occurring malignant subtype.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Within this category, diffuse gliomas are the most frequently occurring malignant subtype

Reference 1

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Source-reported events for the cited work

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

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Observation 8e93df75-b4aa-42b4-9f28-3e329851cc55 · outbound

This paper cites XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder

Reference 2

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

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Observation 66227359-2c01-4511-bf68-d1174d4465bb · outbound

This paper cites Dataset and Implementation Details Our study utilizes the multimodal Brain Tumor Segmentation Challenge (BraTS) 2024 dataset [12].

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Dataset and Implementation Details Our study utilizes the multimodal Brain Tumor Segmentation Challenge (BraTS) 2024 dataset [12]

Reference 3

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

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Observation d0028ead-8dac-478d-8612-23d6661f0b76 · outbound

This paper cites Our model enhances segmentation accuracy and MRI data reconstruction quality by integrating cross-modal encoding, multi-task learning, and attention mechanisms.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Our model enhances segmentation accuracy and MRI data reconstruction quality by integrating cross-modal encoding, multi-task learning, and attention mechanisms

Reference 4

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Source-reported events for the cited work

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

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Observation d8045e0c-58d7-4207-ab26-2840b8d772cd · outbound

This paper cites Ethical approval was not required as con- firmed by the license attached with the open access data.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Ethical approval was not required as con- firmed by the license attached with the open access data

Reference 5

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Source-reported events for the cited work

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

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Observation f7c5fb17-8955-4dc9-854d-d98cc151f571 · outbound

This paper cites A2304), Guangdong Basic and Applied Basic Research Foundation (No.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder A2304), Guangdong Basic and Applied Basic Research Foundation (No

Reference 6

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Source-reported events for the cited work

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

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Observation 05ca6059-85f8-49ce-ac10-0d72c5f824b2 · outbound

This paper cites Auto-Encoding Variational Bayes.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Auto-Encoding Variational Bayes

Reference 7

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Observation 4bd6999b-23d9-4d1c-9101-2f98f49827e3 · outbound

This paper cites Missing mri pulse sequence synthesis using multi-modal generative adversarial network,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Missing mri pulse sequence synthesis using multi-modal generative adversarial network,

Reference 8

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Observation 924d681b-6e91-4a74-a44d-a0ffb4615ed0 · outbound

This paper cites TC-KANRecon: High-Quality and Accelerated MRI Reconstruction via Adaptive KAN Mechanisms and Intelligent Feature Scaling.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder TC-KANRecon: High-Quality and Accelerated MRI Reconstruction via Adaptive KAN Mechanisms and Intelligent Feature Scaling

Reference 9

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Observation 925e594d-cf50-475b-9f88-d1a1a09a501c · outbound

This paper cites Hetero-modal vari- ational encoder-decoder for joint modality completion and segmentation,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Hetero-modal vari- ational encoder-decoder for joint modality completion and segmentation,

Reference 10

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Observation 2c5d5d92-1b1d-4aa0-a5e6-92e3b61b9d2b · outbound

This paper cites M3ae: multimodal representation learning for brain tumor segmentation with missing modalities,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder M3ae: multimodal representation learning for brain tumor segmentation with missing modalities,

Reference 12

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

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Observation d6988683-ecd5-4408-91d0-051cd708a07d · outbound

This paper cites All the baselines and our model were trained and tested using the same backbone network to ensure consistency in the evaluation phase.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder All the baselines and our model were trained and tested using the same backbone network to ensure consistency in the evaluation phase

Reference 13

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Source-reported events for the cited work

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

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Observation 87af52af-b9f3-4862-859b-a50c787384df · outbound

This paper cites Multimodal generative models for scalable weakly-supervised learning,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Multimodal generative models for scalable weakly-supervised learning,

Reference 14

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T19:51:18.272235Z digest=sha256:53f0038bbf17ccedb3b0930114587543890a85ba28a9024f722acd3e28bba037

Observation 7357a2f4-6b17-4278-a250-1b1518e54492 · outbound

This paper cites Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions

Reference 15

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Observation 110c4950-10a7-41e5-abd5-843266cd3c8f · outbound

This paper cites Region-of-interest attentive hetero- modal variational encoder-decoder for segmentation with missing modalities,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Region-of-interest attentive hetero- modal variational encoder-decoder for segmentation with missing modalities,

Reference 16

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

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Observation 659b3729-4b57-4384-a4b9-babfa01605d6 · outbound

This paper cites Vision-LSTM: xLSTM as generic vision backbone,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Vision-LSTM: xLSTM as generic vision backbone,

Reference 17

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Observation 703d07b0-ba83-4096-94e1-85a70a1f0d1c · outbound

This paper cites Dusfe: Dual-channel squeeze-fusion-excitation co-attention for cross-modality registration of cardiac spect and ct,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Dusfe: Dual-channel squeeze-fusion-excitation co-attention for cross-modality registration of cardiac spect and ct,

Reference 18

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Source-reported events for the cited work

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

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Observation a52af394-6ad4-479e-b351-87488e8fbebc · outbound

This paper cites The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:51:18.295396Z digest=sha256:f438ea54ff802e30199695a023e414816a3dc02735fd3d2fc94349a7e7e23dd9

Observation 33d577c1-07e7-4db2-9213-6b9e8ecd635b · outbound

This paper cites Robust multimodal brain tumor segmentation via feature disentanglement and gated fu- sion,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder Robust multimodal brain tumor segmentation via feature disentanglement and gated fu- sion,

Reference 20

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Source-reported events for the cited work

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

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Observation b7011bc6-c400-4976-b45c-d4d309e519c3 · outbound

This paper cites mmformer: Multimodal medical trans- former for incomplete multimodal learning of brain tu- mor segmentation,.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder mmformer: Multimodal medical trans- former for incomplete multimodal learning of brain tu- mor segmentation,

Reference 21

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

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Pith citing papers

Observation 8e93df75-b4aa-42b4-9f28-3e329851cc55 · inbound

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder cites this paper.

XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder

Reference 2

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

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