Paper Citation Record · LEDGER

Boosting Multimodal Learning via Disentangled Gradient Learning

As of 9 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2507.10213.

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

pith.paper-citation-record.v1
2507.10213 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:42:04.308479Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:45:18.800781Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T16:24:55.663925Z

Reference resolution

41 of 41 outbound references displayed

verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ce3e954-3fe8-4a49-98ea-3e173eca0872 · outbound

This paper cites Deep audio-visual speech recognition.

Boosting Multimodal Learning via Disentangled Gradient Learning Deep audio-visual speech recognition

Reference 1

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Observation 76891e0f-6861-4334-9e68-aa74d522bc00 · outbound

This paper cites Look, listen and learn.

Boosting Multimodal Learning via Disentangled Gradient Learning Look, listen and learn

Reference 2

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Observation 111c12ef-2554-4203-8db3-0db81948e3bb · outbound

This paper cites Crema-d: Crowd-sourced emotional multimodal actors dataset.

Boosting Multimodal Learning via Disentangled Gradient Learning Crema-d: Crowd-sourced emotional multimodal actors dataset

Reference 3

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Observation 3dca69b9-94c5-488e-b819-dabcaf1b0fb8 · outbound

This paper cites Shapeconv: Shape- aware convolutional layer for indoor rgb-d semantic segmen- tation.

Boosting Multimodal Learning via Disentangled Gradient Learning Shapeconv: Shape- aware convolutional layer for indoor rgb-d semantic segmen- tation

Reference 4

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Observation 3ff4e644-4a5f-403f-8334-830cb7b4f694 · outbound

This paper cites Vggsound: A large-scale audio-visual dataset.

Boosting Multimodal Learning via Disentangled Gradient Learning Vggsound: A large-scale audio-visual dataset

Reference 5

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Observation 233ea5cb-dfdd-4a00-906e-1ecd9520ea43 · outbound

This paper cites Mars: Motion-augmented rgb stream for action recognition.

Boosting Multimodal Learning via Disentangled Gradient Learning Mars: Motion-augmented rgb stream for action recognition

Reference 6

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Observation 04112079-2f49-4007-a948-94e33c779d7f · outbound

This paper cites Rfnet: Region-aware fusion network for incomplete multi-modal brain tumor seg- mentation.

Boosting Multimodal Learning via Disentangled Gradient Learning Rfnet: Region-aware fusion network for incomplete multi-modal brain tumor seg- mentation

Reference 7

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Observation 380975ab-10e6-47ff-9976-dbb466f96d99 · outbound

This paper cites Improving Multi-Modal Learning with Uni-Modal Teachers.

Boosting Multimodal Learning via Disentangled Gradient Learning Improving Multi-Modal Learning with Uni-Modal Teachers

Reference 8

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Observation d04ad3d6-4560-4391-ad1b-ba395946330d · outbound

This paper cites Pmr: Prototypical modal rebalance for multi- modal learning.

Boosting Multimodal Learning via Disentangled Gradient Learning Pmr: Prototypical modal rebalance for multi- modal learning

Reference 9

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Observation acdb6311-e898-4dcd-b8c5-be5dfaec4ac1 · outbound

This paper cites Modal- ity distillation with multiple stream networks for action recognition.

Boosting Multimodal Learning via Disentangled Gradient Learning Modal- ity distillation with multiple stream networks for action recognition

Reference 10

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Observation 8439a1b3-768b-43b0-b993-0b994e1fdd4e · outbound

This paper cites Multimodal remote sensing benchmark datasets for land cover classification with a shared and spe- cific feature learning model.

Boosting Multimodal Learning via Disentangled Gradient Learning Multimodal remote sensing benchmark datasets for land cover classification with a shared and spe- cific feature learning model

Reference 11

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Observation e14c5cea-3a76-475d-a29e-8c9a3817aab7 · outbound

This paper cites Deep multimodal multilinear fusion with high- order polynomial pooling.

Boosting Multimodal Learning via Disentangled Gradient Learning Deep multimodal multilinear fusion with high- order polynomial pooling

Reference 12

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Observation a4c0bed5-b606-4712-b49f-8e49c2a4b5a2 · outbound

This paper cites Acnet: Attention based network to exploit complementary features for rgbd semantic segmentation.

Boosting Multimodal Learning via Disentangled Gradient Learning Acnet: Attention based network to exploit complementary features for rgbd semantic segmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:05.115144Z

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Observation c8d50297-294c-4dd4-877e-d90e382a8147 · outbound

This paper cites ReconBoost: Boosting Can Achieve Modality Reconcilement.

Boosting Multimodal Learning via Disentangled Gradient Learning ReconBoost: Boosting Can Achieve Modality Reconcilement

Reference 14

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Observation 6ff0afec-753b-4bfe-938c-90dd02a5e640 · outbound

This paper cites Cdnet: Complementary depth network for rgb-d salient object detection.

Boosting Multimodal Learning via Disentangled Gradient Learning Cdnet: Complementary depth network for rgb-d salient object detection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:05.106280Z

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Observation 11dcedba-64a8-4ae9-8738-bd0a34fdee03 · outbound

This paper cites Mmtm: Multimodal transfer module for cnn fusion.

Boosting Multimodal Learning via Disentangled Gradient Learning Mmtm: Multimodal transfer module for cnn fusion

Reference 16

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Observation 55312b4f-189a-4028-8219-5e33ae9bb006 · outbound

This paper cites Boosting multi-modal model performance with adaptive gradient modulation.

Boosting Multimodal Learning via Disentangled Gradient Learning Boosting multi-modal model performance with adaptive gradient modulation

Reference 17

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Observation 5da6ec01-1344-4564-b4ec-74edfdede723 · outbound

This paper cites Multi-modal face anti-spoofing at- tack detection challenge at cvpr2019.

Boosting Multimodal Learning via Disentangled Gradient Learning Multi-modal face anti-spoofing at- tack detection challenge at cvpr2019

Reference 18

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Observation 1dd0b98c-5887-499e-8072-bc9b37550184 · outbound

This paper cites Recognizing human ac- tions as the evolution of pose estimation maps.

Boosting Multimodal Learning via Disentangled Gradient Learning Recognizing human ac- tions as the evolution of pose estimation maps

Reference 19

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Observation 5d092045-0f69-42b0-8bfa-e1cd241ccb71 · outbound

This paper cites librosa: Audio and music signal analysis in python.

Boosting Multimodal Learning via Disentangled Gradient Learning librosa: Audio and music signal analysis in python

Reference 20

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Observation f86af440-804c-42eb-8f88-84a456570335 · outbound

This paper cites Balanced multimodal learning via on-the-fly gradient modulation.

Boosting Multimodal Learning via Disentangled Gradient Learning Balanced multimodal learning via on-the-fly gradient modulation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:05.058046Z

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Observation 5850f270-ecd7-46c2-89a0-6268dd79cc14 · outbound

This paper cites End-to- end audiovisual speech recognition.

Boosting Multimodal Learning via Disentangled Gradient Learning End-to- end audiovisual speech recognition

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:05.049148Z

Source-reported events for the cited work

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Observation 162da72a-423e-458e-bbda-71f022f1e950 · outbound

This paper cites Efficient rgb-d seman- tic segmentation for indoor scene analysis.

Boosting Multimodal Learning via Disentangled Gradient Learning Efficient rgb-d seman- tic segmentation for indoor scene analysis

Reference 23

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Observation ca0a9b3e-3c2c-44a0-a8fa-cbb225ab5b18 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Boosting Multimodal Learning via Disentangled Gradient Learning Indoor segmentation and support inference from rgbd images

Reference 24

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Observation 4bcf7605-00a9-44e3-9ba9-d164dde21c99 · outbound

This paper cites Cubemlp: An mlp-based model for multimodal sentiment analysis and depression estimation.

Boosting Multimodal Learning via Disentangled Gradient Learning Cubemlp: An mlp-based model for multimodal sentiment analysis and depression estimation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:05.019267Z

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Observation 19b91aaf-d98a-4839-8c28-01fd9b4b9262 · outbound

This paper cites Deep rgb-d saliency detection with depth-sensitive attention and automatic multi-modal fusion.

Boosting Multimodal Learning via Disentangled Gradient Learning Deep rgb-d saliency detection with depth-sensitive attention and automatic multi-modal fusion

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:05.009293Z

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Observation 423a94eb-eda4-4324-acfa-66516221871d · outbound

This paper cites Aligning audiovisual features for audiovisual speech recognition.

Boosting Multimodal Learning via Disentangled Gradient Learning Aligning audiovisual features for audiovisual speech recognition

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:04.999072Z

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Observation 643c19c5-4719-4c19-89bb-7afcc1dd4c5d · outbound

This paper cites What makes train- ing multi-modal classification networks hard? In Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 12695–12705, 2020.

Boosting Multimodal Learning via Disentangled Gradient Learning What makes train- ing multi-modal classification networks hard? In Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 12695–12705, 2020

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:04.990090Z

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Observation 74bce552-171b-4f55-b6fd-8cfd1107ed4d · outbound

This paper cites Mmanet: Margin- aware distillation and modality-aware regularization for in- complete multimodal learning.

Boosting Multimodal Learning via Disentangled Gradient Learning Mmanet: Margin- aware distillation and modality-aware regularization for in- complete multimodal learning

Reference 29

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Observation 7aa45e91-2d10-43a4-a9e6-67329199fd57 · outbound

This paper cites Msh- net: Modality-shared hallucination with joint adaptation dis- tillation for remote sensing image classification using miss- ing modalities.

Boosting Multimodal Learning via Disentangled Gradient Learning Msh- net: Modality-shared hallucination with joint adaptation dis- tillation for remote sensing image classification using miss- ing modalities

Reference 30

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Observation d4795f3d-a0dc-44db-8b56-bea49b870e76 · outbound

This paper cites Ro- bust multimodal learning via representation decoupling.

Boosting Multimodal Learning via Disentangled Gradient Learning Ro- bust multimodal learning via representation decoupling

Reference 31

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Observation d54e3bec-5d76-4be8-9c22-7e5c7b69b99c · outbound

This paper cites MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance.

Boosting Multimodal Learning via Disentangled Gradient Learning MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance

Reference 32

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Observation b0cdbcd3-4aa4-4d27-b288-e1d67e9e8d9b · outbound

This paper cites Diagnos- ing and re-learning for balanced multimodal learning.

Boosting Multimodal Learning via Disentangled Gradient Learning Diagnos- ing and re-learning for balanced multimodal learning

Reference 33

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This paper cites A discriminative feature learning approach for deep face recog- nition.

Boosting Multimodal Learning via Disentangled Gradient Learning A discriminative feature learning approach for deep face recog- nition

Reference 34

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Observation a2ad0265-1475-4d5e-843d-b9be69f94120 · outbound

This paper cites A comprehensive study on center loss for deep face recogni- tion.

Boosting Multimodal Learning via Disentangled Gradient Learning A comprehensive study on center loss for deep face recogni- tion

Reference 35

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Observation 2a5f7ef6-a917-4601-8fc3-5c6781090374 · outbound

This paper cites Mmcosine: Multi-modal cosine loss towards balanced audio-visual fine-grained learning.

Boosting Multimodal Learning via Disentangled Gradient Learning Mmcosine: Multi-modal cosine loss towards balanced audio-visual fine-grained learning

Reference 36

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Observation 87cccb0a-4d54-4af5-b56c-521178c7b8ee · outbound

This paper cites Tensor Fusion Network for Multimodal Sentiment Analysis.

Boosting Multimodal Learning via Disentangled Gradient Learning Tensor Fusion Network for Multimodal Sentiment Analysis

Reference 37

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This paper cites Multi-attention recurrent network for human communication comprehen- sion.

Boosting Multimodal Learning via Disentangled Gradient Learning Multi-attention recurrent network for human communication comprehen- sion

Reference 38

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This paper cites Multimodal Representation Learning by Alternating Unimodal Adaptation.

Boosting Multimodal Learning via Disentangled Gradient Learning Multimodal Representation Learning by Alternating Unimodal Adaptation

Reference 39

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This paper cites mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation.

Boosting Multimodal Learning via Disentangled Gradient Learning mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation

Reference 40

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This paper cites Rgb-d salient object detection: A sur- vey.

Boosting Multimodal Learning via Disentangled Gradient Learning Rgb-d salient object detection: A sur- vey

Reference 41

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Pith citing papers

Observation 3a935e74-6a33-4dad-b7ff-9d17661416e3 · inbound

No Data? No Problem: Robust Vision-Tabular Learning with Missing Values cites this paper.

No Data? No Problem: Robust Vision-Tabular Learning with Missing Values Boosting Multimodal Learning via Disentangled Gradient Learning

Reference 30

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Observation a8263927-8c55-4a53-9a7f-fb610c31d7af · inbound

Balancing Multimodal Learning through Label Space Reshaping cites this paper.

Balancing Multimodal Learning through Label Space Reshaping Boosting Multimodal Learning via Disentangled Gradient Learning

Reference 30

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Source-reported events for the cited work

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