Paper Citation Record · LEDGER

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations

As of 7 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2507.03304.

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

pith.paper-citation-record.v1
2507.03304 v1

Coverage vector

measured 58 of 58 reference resolution

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measured 60 of 60 standing notices

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: pith, observed 2026-08-05T21:53:33.960468Z

Reference resolution

58 of 58 outbound references displayed

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External citation measurements

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Outbound references

Observation 367629b1-06fd-44bf-8af8-a12ad636b06d · outbound

This paper cites Robust cross-modal representation learning with progressive self- distillation.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Robust cross-modal representation learning with progressive self- distillation

Reference 1

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This paper cites Person30k: A dual-meta general- ization network for person re-identification.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Person30k: A dual-meta general- ization network for person re-identification

Reference 2

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This paper cites Ex- ploiting domain-specific features to enhance domain gener- alization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Ex- ploiting domain-specific features to enhance domain gener- alization

Reference 3

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This paper cites Domain generalization by solving jigsaw puzzles.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Domain generalization by solving jigsaw puzzles

Reference 4

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Observation 83fe79c4-12a6-4c3f-8875-4dce30852bc1 · outbound

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

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Vggsound: A large-scale audio-visual dataset

Reference 5

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Observation ca91e6ad-7b25-4850-ba6a-1cd22ec982d5 · outbound

This paper cites Uniter: Universal image-text representation learning.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Uniter: Universal image-text representation learning

Reference 6

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This paper cites Club: A contrastive log-ratio up- per bound of mutual information.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Club: A contrastive log-ratio up- per bound of mutual information

Reference 7

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Observation 7235d909-7359-4f44-a604-e0d0da7610e4 · outbound

This paper cites Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening

Reference 8

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This paper cites Openmmlab’s next generation video understanding toolbox and benchmark.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Openmmlab’s next generation video understanding toolbox and benchmark

Reference 9

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Observation 0d48e055-6574-4c8c-9a5b-3142ba062454 · outbound

This paper cites Scaling egocentric vision: The epic-kitchens dataset.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Scaling egocentric vision: The epic-kitchens dataset

Reference 10

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Observation d1ec1c8e-4551-4c30-8080-8f31d01b84cd · outbound

This paper cites Simmmdg: A simple and effective framework for multi-modal domain generalization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Simmmdg: A simple and effective framework for multi-modal domain generalization

Reference 11

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Observation 8136cfee-7770-41b1-be7e-ae6e20088cf3 · outbound

This paper cites Towards mul- timodal open-set domain generalization and adaptation through self-supervision.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Towards mul- timodal open-set domain generalization and adaptation through self-supervision

Reference 12

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This paper cites Multi-modal align- ment using representation codebook.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Multi-modal align- ment using representation codebook

Reference 13

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This paper cites Cross-modal representation flattening for multi-modal do- main generalization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Cross-modal representation flattening for multi-modal do- main generalization

Reference 14

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Observation 40d239d3-9cd2-4cac-a313-79ab721ea3d0 · outbound

This paper cites Ace: A generative cross-modal retrieval framework with coarse-to-fine semantic modeling.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Ace: A generative cross-modal retrieval framework with coarse-to-fine semantic modeling

Reference 15

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Observation 32bfe891-36d2-4b79-a35d-3dd57f575f5d · outbound

This paper cites Slowfast networks for video recognition.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Slowfast networks for video recognition

Reference 16

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Observation 5aab43cb-8fb3-423a-9c37-4e3974d0e37e · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 17

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This paper cites Domain-adversarial training of neural networks.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Domain-adversarial training of neural networks

Reference 18

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This paper cites Imagebind: One embedding space to bind them all.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Imagebind: One embedding space to bind them all

Reference 19

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This paper cites Learning Shared Semantic Space for Speech-to-Text Translation.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Learning Shared Semantic Space for Speech-to-Text Translation

Reference 20

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This paper cites Mixgen: A new multi- modal data augmentation.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Mixgen: A new multi- modal data augmentation

Reference 21

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This paper cites Deep residual learning for image recognition.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Deep residual learning for image recognition

Reference 22

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This paper cites Enhancing Multimodal Unified Representations for Cross Modal Generalization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Enhancing Multimodal Unified Representations for Cross Modal Generalization

Reference 23

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Semantic residual for multimodal unified discrete representation

Reference 24

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This paper cites Overcoming both domain shift and label shift for referring video segmentation.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Overcoming both domain shift and label shift for referring video segmentation

Reference 25

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

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Modality competition: What makes joint training of multi-modal network fail in deep learn- ing?(provably)

Reference 26

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This paper cites Self-challenging improves cross-domain generalization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Self-challenging improves cross-domain generalization

Reference 27

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This paper cites The Kinetics Human Action Video Dataset.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations The Kinetics Human Action Video Dataset

Reference 28

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Supervised contrastive learning

Reference 29

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Learning to generalize: Meta-learning for do- main generalization

Reference 30

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This paper cites Domain generalization for med- ical imaging classification with linear-dependency regular- ization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Domain generalization for med- ical imaging classification with linear-dependency regular- ization

Reference 31

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This paper cites Cross-Modal Discrete Representation Learning.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Cross-Modal Discrete Representation Learning

Reference 32

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This paper cites Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous fre- quency space.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous fre- quency space

Reference 33

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Unified-io: A unified model for vision, language, and multi-modal tasks

Reference 34

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This paper cites Do- main generalisation via risk distribution matching.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Do- main generalisation via risk distribution matching

Reference 35

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Unsupervised learning of visual representations by solving jigsaw puzzles

Reference 36

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This paper cites Causality-inspired single- source domain generalization for medical image segmenta- tion.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Causality-inspired single- source domain generalization for medical image segmenta- tion

Reference 37

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Two at once: Enhancing learning and generalization capacities via ibn-net

Reference 38

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Audio-visual speech recognition with a hybrid ctc/attention architecture

Reference 39

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This paper cites Domain generalization through audio- visual relative norm alignment in first person action recog- nition.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Domain generalization through audio- visual relative norm alignment in first person action recog- nition

Reference 40

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This paper cites Learn- ing transferable visual models from natural language super- vision.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Learn- ing transferable visual models from natural language super- vision

Reference 41

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This paper cites Domain generalization of 3d semantic segmenta- tion in autonomous driving.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Domain generalization of 3d semantic segmenta- tion in autonomous driving

Reference 42

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Xkd: Cross-modal knowl- edge distillation with domain alignment for video represen- tation learning

Reference 43

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Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Domain randomization for transferring deep neural networks from simulation to the real world

Reference 44

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This paper cites Deep Domain Confusion: Maximizing for Domain Invariance.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Deep Domain Confusion: Maximizing for Domain Invariance

Reference 45

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This paper cites IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models

Reference 46

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This paper cites Generalizing to unseen domains: A survey on do- main generalization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Generalizing to unseen domains: A survey on do- main generalization

Reference 47

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This paper cites Towards Transformer-Based Aligned Generation with Self-Coherence Guidance.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Towards Transformer-Based Aligned Generation with Self-Coherence Guidance

Reference 48

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This paper cites Vlmixer: Unpaired vision-language pre-training via cross-modal cutmix.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Vlmixer: Unpaired vision-language pre-training via cross-modal cutmix

Reference 49

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This paper cites Achiev- ing cross modal generalization with multimodal unified rep- resentation.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Achiev- ing cross modal generalization with multimodal unified rep- resentation

Reference 50

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This paper cites mixup: Beyond Empirical Risk Minimization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations mixup: Beyond Empirical Risk Minimization

Reference 51

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Observation c78852ac-f983-4f70-9ce7-22d74d7406c8 · outbound

This paper cites Towards effective multi-modal interchanges in zero-resource sounding object localization.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Towards effective multi-modal interchanges in zero-resource sounding object localization

Reference 52

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Observation 274f3c99-efa3-4402-8f0c-0942b630b3b1 · outbound

This paper cites Deep domain-adversarial image generation for do- main generalisation.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Deep domain-adversarial image generation for do- main generalisation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:17:33.998204Z

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Observation ce04ae21-10af-465f-a1ce-205d586acd9b · outbound

This paper cites The feature dimensions for video, audio, and optical flow are 2304, 512, and 2048, respec- tively.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations The feature dimensions for video, audio, and optical flow are 2304, 512, and 2048, respec- tively

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:17:33.987896Z

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Observation 198db991-3e51-4860-aba8-d3d4dc5bb88c · outbound

This paper cites In contrast, our proposed approach sub- stantially improves their performance in the MMDG set- ting.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations In contrast, our proposed approach sub- stantially improves their performance in the MMDG set- ting

Reference 55

Resolution: verified exact; raw_fallback, observed 2026-08-06T20:17:33.826037Z

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Observation 39431b76-be70-446e-9b0d-6c8f699dff9e · outbound

This paper cites Notably, our method exhibits minimal fluctuations across all parame- ter settings, indicating a lower sensitivity to hyperparameter selection.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations Notably, our method exhibits minimal fluctuations across all parame- ter settings, indicating a lower sensitivity to hyperparameter selection

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:17:33.977922Z

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Observation f164fdb5-87d3-4fab-b0a4-8b278bc93993 · outbound

This paper cites We do not ab- late Lcls since it is essential for classification.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations We do not ab- late Lcls since it is essential for classification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:17:33.968234Z

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Observation 19bb939f-7ff0-444f-99ea-caac1b72b22b · outbound

This paper cites It can be observed that the gen- eral and specific information of each modality are well- separated and consistently aligned across domains.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations It can be observed that the gen- eral and specific information of each modality are well- separated and consistently aligned across domains

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:17:33.959004Z

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Pith citing papers

Observation bdc993b6-96dd-4fdc-b61a-fd7b27d75e34 · inbound

Open-set Cross Modal Generalization via Multimodal Unified Representation cites this paper.

Open-set Cross Modal Generalization via Multimodal Unified Representation Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations

Reference 24

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Observation 211054c5-9651-4fd4-aa8f-cb0ac8b06d73 · inbound

TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal cites this paper.

TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations

Reference 20

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