Paper Citation Record · LEDGER

Improving Multimodal Learning Balance and Sufficiency through Data Remixing

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.11550.

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

pith.paper-citation-record.v1
2506.11550 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:10:26.201549Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

40 of 40 outbound references displayed

verified exact1
verified fuzzy20
unresolved19
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a548648-f9e1-474f-bea7-08474783b0d5 · outbound

This paper cites write newline.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing write newline

Reference 1

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Source-reported events for the cited work

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Observation a37b3747-9691-4892-aaf4-a8838f5588c3 · outbound

This paper cites and Zisserman, A.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing and Zisserman, A

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef675764-2246-43ac-9302-17998766915c · outbound

This paper cites G., Keutmann, M.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing G., Keutmann, M

Reference 3

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Source-reported events for the cited work

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Observation 3a4a5f74-4125-4b6d-a635-0aaaf7dbd6b4 · outbound

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

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Improving Multi-Modal Learning with Uni-Modal Teachers

Reference 4

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Source-reported events for the cited work

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Observation 1b778fed-948f-4364-9a02-7a15a5b8d1dd · outbound

This paper cites On uni-modal feature learning in supervised multi-modal learning.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing On uni-modal feature learning in supervised multi-modal learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:30.581147Z

Source-reported events for the cited work

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Observation d32cf719-3579-4c31-808a-781c5b578f4f · outbound

This paper cites Pmr: Prototypical modal rebalance for multimodal learning.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Pmr: Prototypical modal rebalance for multimodal learning

Reference 6

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Source-reported events for the cited work

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Observation 0ac5d141-ba34-432e-a46b-bdce2cb1aa30 · outbound

This paper cites Multimodal imbalance-aware gradient modulation for weakly-supervised audio-visual video parsing.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Multimodal imbalance-aware gradient modulation for weakly-supervised audio-visual video parsing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:30.536474Z

Source-reported events for the cited work

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Observation 3d89c427-7763-4a34-8d2c-90e16c49c61f · outbound

This paper cites and Zou, J.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing and Zou, J

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:30.501756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4c371302-6473-4e1a-9c27-2220902b6e49 · outbound

This paper cites and Piccardi, M.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing and Piccardi, M

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:30.171070Z

Source-reported events for the cited work

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Observation ead9fb94-6b5e-4e7d-a6fa-451af295da41 · outbound

This paper cites Deep residual learning for image recognition.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Deep residual learning for image recognition

Reference 10

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Source-reported events for the cited work

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Observation 49f68553-7711-4e61-a2b9-55abf0f5cece · outbound

This paper cites Multimodal temporal attention in sentiment analysis.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Multimodal temporal attention in sentiment analysis

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:29.842232Z

Source-reported events for the cited work

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Observation 1948d1d7-4c49-4f0f-8181-5ecd58202e3b · outbound

This paper cites Improving neural networks by preventing co-adaptation of feature detectors.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Improving neural networks by preventing co-adaptation of feature detectors

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:10:23.380389Z

Source-reported events for the cited work

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Observation 32cd2ecb-c47d-4db9-be75-b762e021b3b7 · outbound

This paper cites Modality competition: What makes joint training of multi-modal network fail in deep learning?(provably).

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Modality competition: What makes joint training of multi-modal network fail in deep learning?(provably)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T04:10:23.489321Z

Source-reported events for the cited work

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Observation 32118ad0-dc20-42cb-a51f-290795e1db07 · outbound

This paper cites an unresolved cited work.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Unresolved cited work

Reference 14

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Source-reported events for the cited work

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Observation 5fc06bc0-4b0f-4b26-8797-9a98b0e95f33 · outbound

This paper cites The Kinetics Human Action Video Dataset.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing The Kinetics Human Action Video Dataset

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:10:23.745725Z

Source-reported events for the cited work

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Observation c70e264f-0b6b-4362-bcac-496f4c08b55a · outbound

This paper cites Efficient large-scale multi-modal classification.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Efficient large-scale multi-modal classification

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:29.594072Z

Source-reported events for the cited work

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Observation 829b936d-f245-4217-b538-1bef5d29f346 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Adam: A Method for Stochastic Optimization

Reference 17

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Source-reported events for the cited work

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Observation cd2bdb4f-e0cb-4b42-bdf5-ff41b9ad5c0b · outbound

This paper cites Improving Multimodal Learning with Multi-Loss Gradient Modulation.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Improving Multimodal Learning with Multi-Loss Gradient Modulation

Reference 18

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Source-reported events for the cited work

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Observation 2933294e-1119-451e-8bef-39f6d905a80b · outbound

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

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Boosting multi-modal model performance with adaptive gradient modulation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:29.375825Z

Source-reported events for the cited work

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Observation e0d6d25b-6979-43dd-ad18-4559de3f7fb9 · outbound

This paper cites Variational Probabilistic Fusion Network for RGB-T Semantic Segmentation.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Variational Probabilistic Fusion Network for RGB-T Semantic Segmentation

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:10:26.448724Z

Source-reported events for the cited work

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Observation 96529e4a-2b61-424a-b6d0-e66114088001 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 21

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Observation 73ac3bbb-77bb-44f7-85c7-7adf0d51a014 · outbound

This paper cites Y., et al.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Y., et al

Reference 22

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Source-reported events for the cited work

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Observation cfeb68f4-f573-4ade-85c5-d9de5a4c8155 · outbound

This paper cites and Efros, A.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing and Efros, A

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:29.058207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8fb4b2a3-62e0-4ad5-8ecb-be3c553a1945 · outbound

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

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Balanced multimodal learning via on-the-fly gradient modulation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:10:24.830032Z

Source-reported events for the cited work

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Observation 1baf4fb1-0daa-4f07-a19e-20c88c4711f3 · outbound

This paper cites Film: Visual reasoning with a general conditioning layer.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Film: Visual reasoning with a general conditioning layer

Reference 25

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Source-reported events for the cited work

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Observation 05f3c57a-e8e3-46ab-b66c-22c2b7e279cd · outbound

This paper cites Graph interactive network with adaptive gradient for multi-modal rumor detection.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Graph interactive network with adaptive gradient for multi-modal rumor detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:28.859950Z

Source-reported events for the cited work

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Observation d590d297-cad3-497b-9b2f-61a353e0f4cd · outbound

This paper cites Learning to balance the learning rates between various modalities via adaptive tracking factor.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Learning to balance the learning rates between various modalities via adaptive tracking factor

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:28.674407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b34001e-84c2-4555-b6f7-721dbb80dc7e · outbound

This paper cites and Hinton, G.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing and Hinton, G

Reference 28

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Source-reported events for the cited work

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Observation 288b2044-a7b1-4cb0-b9cf-28828a11a4d8 · outbound

This paper cites Centralnet: a multilayer approach for multimodal fusion.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Centralnet: a multilayer approach for multimodal fusion

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:28.487663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7fb419c-4dec-44d9-9bf6-b689ff1b43ac · outbound

This paper cites What makes training multi-modal classification networks hard? In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.\ 12695--12705, 2020.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing What makes training multi-modal classification networks hard? In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.\ 12695--12705, 2020

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:28.330146Z

Source-reported events for the cited work

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Observation 5c509e4e-dfa4-401d-a12a-3cdbe95f0733 · outbound

This paper cites and Hu, D.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing and Hu, D

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:28.135413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8ce45d74-709e-4ecd-b3ec-b2aef8c70c21 · outbound

This paper cites Enhancing multimodal cooperation via sample-level modality valuation.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Enhancing multimodal cooperation via sample-level modality valuation

Reference 32

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Source-reported events for the cited work

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Observation 29b606e7-f28d-40b4-8212-01f0a0aff8ff · outbound

This paper cites Diagnosing and re-learning for balanced multimodal learning.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Diagnosing and re-learning for balanced multimodal learning

Reference 33

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Observation a9bae4a8-d686-43d7-bb35-31a1417d66df · outbound

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Improving Multimodal Learning Balance and Sufficiency through Data Remixing Unresolved cited work

Reference 34

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Observation 1a3b309f-37d9-476f-b68c-ae2d1a87ea43 · outbound

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

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Mmcosine: Multi-modal cosine loss towards balanced audio-visual fine-grained learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:27.768250Z

Source-reported events for the cited work

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Observation 605b493c-a82f-42e1-90fd-fe0e7eb854fe · outbound

This paper cites Mcl: A contrastive learning method for multimodal data fusion in violence detection.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Mcl: A contrastive learning method for multimodal data fusion in violence detection

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:27.580294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1c9965ad-39f0-4d8c-ae8e-101dd49b6895 · outbound

This paper cites Multimodal Fusion on Low-quality Data: A Comprehensive Survey.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Multimodal Fusion on Low-quality Data: A Comprehensive Survey

Reference 37

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Source-reported events for the cited work

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Observation e1544be6-de22-4c7b-9047-00e9578606a1 · outbound

This paper cites Multimodal representation learning by alternating unimodal adaptation.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Multimodal representation learning by alternating unimodal adaptation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:27.355798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b6ee059-eb55-4e7d-81ed-512085d0e225 · outbound

This paper cites Adaptive mask co-optimization for modal dependence in multimodal learning.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Adaptive mask co-optimization for modal dependence in multimodal learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:27.048028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af26b6f3-d4ed-4fa4-9486-f6282cc8deac · outbound

This paper cites Vision+ x: A survey on multimodal learning in the light of data.

Improving Multimodal Learning Balance and Sufficiency through Data Remixing Vision+ x: A survey on multimodal learning in the light of data

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:10:26.779388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.