Paper Citation Record · LEDGER

Open-set Cross Modal Generalization via Multimodal Unified Representation

As of 7 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:2507.14935.

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

pith.paper-citation-record.v1
2507.14935 v1

Coverage vector

measured 65 of 65 reference resolution

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measured 66 of 66 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:53:28.021948Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T21:53:34.084878Z

Reference resolution

65 of 65 outbound references displayed

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External citation measurements

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Outbound references

Observation 9a653eda-7ed8-461e-9c05-254125e640ed · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Robust cross-modal representation learning with progressive self- distillation

Reference 1

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This paper cites On the effectiveness of image rotation for open set domain adaptation.

Open-set Cross Modal Generalization via Multimodal Unified Representation On the effectiveness of image rotation for open set domain adaptation

Reference 2

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This paper cites Domain generalization by solving jigsaw puzzles.

Open-set Cross Modal Generalization via Multimodal Unified Representation Domain generalization by solving jigsaw puzzles

Reference 3

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This paper cites Collecting highly paral- lel data for paraphrase evaluation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Collecting highly paral- lel data for paraphrase evaluation

Reference 4

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Observation 396e61a4-d780-417d-a576-1fbeb402b0c1 · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Vggsound: A large-scale audio-visual dataset

Reference 5

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Observation 40a90f4a-be71-4554-a7b7-24b51ec6dc28 · outbound

This paper cites Hts-at: A hierarchi- cal token-semantic audio transformer for sound classifica- tion and detection.

Open-set Cross Modal Generalization via Multimodal Unified Representation Hts-at: A hierarchi- cal token-semantic audio transformer for sound classifica- tion and detection

Reference 6

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Observation 9eacc5aa-1288-437f-a5f3-2e665af6c317 · outbound

This paper cites VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset.

Open-set Cross Modal Generalization via Multimodal Unified Representation VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset

Reference 7

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Observation 4528c55e-2a93-4781-ae74-7c72c085ea0e · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Uniter: Universal image-text representation learning

Reference 8

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This paper cites Sinkd: Sinkhorn distance minimization for knowledge distillation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Sinkd: Sinkhorn distance minimization for knowledge distillation

Reference 9

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This paper cites Sinkhorn distance minimization for knowledge distilla- tion.

Open-set Cross Modal Generalization via Multimodal Unified Representation Sinkhorn distance minimization for knowledge distilla- tion

Reference 10

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This paper cites Optical: Leveraging optimal trans- port for contribution allocation in dataset distillation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Optical: Leveraging optimal trans- port for contribution allocation in dataset distillation

Reference 11

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This paper cites Layoutenc: Leveraging enhanced layout rep- resentations for transformer-based complex scene synthesis.

Open-set Cross Modal Generalization via Multimodal Unified Representation Layoutenc: Leveraging enhanced layout rep- resentations for transformer-based complex scene synthesis

Reference 12

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This paper cites Streetsurfgs: Scalable ur- ban street surface reconstruction with planar-based gaussian splatting.

Open-set Cross Modal Generalization via Multimodal Unified Representation Streetsurfgs: Scalable ur- ban street surface reconstruction with planar-based gaussian splatting

Reference 13

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Observation af806a17-5526-4171-8036-6b1e99c5917e · outbound

This paper cites Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision.

Open-set Cross Modal Generalization via Multimodal Unified Representation Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision

Reference 14

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Observation 33e87a74-1eb6-464c-b70a-86a9749d9f10 · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Simmmdg: A simple and effective framework for multi-modal domain generalization

Reference 15

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Observation 507023a4-0327-44b5-b8ea-a620ee805697 · outbound

This paper cites Clotho: An audio captioning dataset.

Open-set Cross Modal Generalization via Multimodal Unified Representation Clotho: An audio captioning dataset

Reference 16

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Multi-modal align- ment using representation codebook

Reference 17

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Ace: A generative cross-modal retrieval framework with coarse-to-fine semantic modeling

Reference 18

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This paper cites Slowfast networks for video recognition.

Open-set Cross Modal Generalization via Multimodal Unified Representation Slowfast networks for video recognition

Reference 19

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This paper cites Domain-adversarial training of neural networks.

Open-set Cross Modal Generalization via Multimodal Unified Representation Domain-adversarial training of neural networks

Reference 20

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Imagebind: One embedding space to bind them all

Reference 21

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Observation 5693eb52-ffb9-4a0e-a0b6-c3fd604f14b2 · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Enhancing Multimodal Unified Representations for Cross Modal Generalization

Reference 22

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This paper cites Semantic residual for multimodal unified discrete representation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Semantic residual for multimodal unified discrete representation

Reference 23

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This paper cites Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations.

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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This paper cites WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling.

Open-set Cross Modal Generalization via Multimodal Unified Representation WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling

Reference 25

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This paper cites Learning to generalize: Meta-learning for do- main generalization.

Open-set Cross Modal Generalization via Multimodal Unified Representation Learning to generalize: Meta-learning for do- main generalization

Reference 26

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Domain generalization for med- ical imaging classification with linear-dependency regular- ization

Reference 27

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This paper cites Adjustment and alignment for unbiased open set domain adaptation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Adjustment and alignment for unbiased open set domain adaptation

Reference 28

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This paper cites Cross-Modal Discrete Representation Learning.

Open-set Cross Modal Generalization via Multimodal Unified Representation Cross-Modal Discrete Representation Learning

Reference 29

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous fre- quency space

Reference 30

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Open-set Cross Modal Generalization via Multimodal Unified Representation Swin transformer: Hierarchical vision transformer using shifted windows

Reference 31

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This paper cites Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks.

Open-set Cross Modal Generalization via Multimodal Unified Representation Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks

Reference 32

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Open-set Cross Modal Generalization via Multimodal Unified Representation Unsupervised learning of visual representations by solving jigsaw puzzles

Reference 33

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Open-set Cross Modal Generalization via Multimodal Unified Representation Two at once: Enhancing learning and generalization capacities via ibn-net

Reference 34

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Open-set Cross Modal Generalization via Multimodal Unified Representation Estimating Visual Information From Audio Through Manifold Learning

Reference 35

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Open-set Cross Modal Generalization via Multimodal Unified Representation Audio-visual speech recognition with a hybrid ctc/attention architecture

Reference 36

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Domain generalization through audio- visual relative norm alignment in first person action recog- nition

Reference 37

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This paper cites Learning transferable visual models from natural language supervi- sion.

Open-set Cross Modal Generalization via Multimodal Unified Representation Learning transferable visual models from natural language supervi- sion

Reference 38

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Open-set Cross Modal Generalization via Multimodal Unified Representation Mask2anomaly: Mask transformer for uni- versal open-set segmentation

Reference 39

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This paper cites XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning.

Open-set Cross Modal Generalization via Multimodal Unified Representation XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning

Reference 40

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This paper cites Open domain generalization with domain- augmented meta-learning.

Open-set Cross Modal Generalization via Multimodal Unified Representation Open domain generalization with domain- augmented meta-learning

Reference 41

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This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

Open-set Cross Modal Generalization via Multimodal Unified Representation UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 42

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Open-set Cross Modal Generalization via Multimodal Unified Representation Audio-visual event localization in unconstrained videos

Reference 43

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This paper cites Unified mul- tisensory perception: Weakly-supervised audio-visual video parsing.

Open-set Cross Modal Generalization via Multimodal Unified Representation Unified mul- tisensory perception: Weakly-supervised audio-visual video parsing

Reference 44

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This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.

Open-set Cross Modal Generalization via Multimodal Unified Representation Domain randomization for transferring deep neural networks from simulation to the real world

Reference 45

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Deep Domain Confusion: Maximizing for Domain Invariance

Reference 46

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

Open-set Cross Modal Generalization via Multimodal Unified Representation IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models

Reference 47

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

Open-set Cross Modal Generalization via Multimodal Unified Representation 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.

Open-set Cross Modal Generalization via Multimodal Unified Representation Vlmixer: Unpaired vision-language pre-training via cross-modal cutmix

Reference 49

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This paper cites General- izable decision boundaries: Dualistic meta-learning for open set domain generalization.

Open-set Cross Modal Generalization via Multimodal Unified Representation General- izable decision boundaries: Dualistic meta-learning for open set domain generalization

Reference 50

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 820ec6f5-c22a-461a-9ce0-6d02045a981c · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Achiev- ing cross modal generalization with multimodal unified rep- resentation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:39.140480Z

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Observation 19e3608f-e6cf-420e-aaaa-a654c73fda0a · outbound

This paper cites Hyper- spectral image classification based on unsupervised hetero- geneous domain adaptation cyclegan.

Open-set Cross Modal Generalization via Multimodal Unified Representation Hyper- spectral image classification based on unsupervised hetero- geneous domain adaptation cyclegan

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:38.914667Z

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Observation 5d2da7bd-d3ac-45e0-a4d3-cf220f061a64 · outbound

This paper cites Class semantics modulation for open-set in- stance segmentation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Class semantics modulation for open-set in- stance segmentation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:38.668841Z

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Observation 0c7c5007-6929-411b-8fac-ce29d6d3443e · outbound

This paper cites Learn- ing domain-invariant and discriminative features for homo- geneous unsupervised domain adaptation.

Open-set Cross Modal Generalization via Multimodal Unified Representation Learn- ing domain-invariant and discriminative features for homo- geneous unsupervised domain adaptation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:38.436124Z

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Observation c55857b4-5572-411e-8a7d-b081986d96b4 · outbound

This paper cites A du- ality based approach for realtime tv-l 1 optical flow.

Open-set Cross Modal Generalization via Multimodal Unified Representation A du- ality based approach for realtime tv-l 1 optical flow

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:38.192212Z

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Observation 7f10b910-2872-4c0b-8b06-b8d5b1dc0448 · outbound

This paper cites mixup: Beyond empirical risk management.

Open-set Cross Modal Generalization via Multimodal Unified Representation mixup: Beyond empirical risk management

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:37.927785Z

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Observation 78b6b8c4-a9aa-4cd1-91a4-8751551b2670 · outbound

This paper cites Extending multi-modal contrastive rep- resentations.

Open-set Cross Modal Generalization via Multimodal Unified Representation Extending multi-modal contrastive rep- resentations

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:37.701085Z

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Observation 92ae4c94-4bfa-47f6-af31-dc2573259f2d · outbound

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

Open-set Cross Modal Generalization via Multimodal Unified Representation Towards effective multi-modal interchanges in zero-resource sounding object localization

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:37.459916Z

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Observation 55de53c6-1ece-419d-9a92-e46d4b6bf367 · outbound

This paper cites Positive sample propagation along the audio- visual event line.

Open-set Cross Modal Generalization via Multimodal Unified Representation Positive sample propagation along the audio- visual event line

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:37.179781Z

Source-reported events for the cited work

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Observation 97ddbd13-ffc0-4fa6-b81a-5493df3479fa · outbound

This paper cites Contrastive pos- itive sample propagation along the audio-visual event line.

Open-set Cross Modal Generalization via Multimodal Unified Representation Contrastive pos- itive sample propagation along the audio-visual event line

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:36.975633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9e964db3-0843-4c9d-8e06-6d5cebaacee9 · outbound

This paper cites As shown in Figure 4, applying the same mask to paired multimodal samples helps improve model perfor- mance.

Open-set Cross Modal Generalization via Multimodal Unified Representation As shown in Figure 4, applying the same mask to paired multimodal samples helps improve model perfor- mance

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:36.711555Z

Source-reported events for the cited work

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Observation ea7d8129-f526-46f0-a843-fcf27af389a9 · outbound

This paper cites As shown in Figure 5, we experimented with five different settings: 256, 400, 512, 800, and 1024.

Open-set Cross Modal Generalization via Multimodal Unified Representation As shown in Figure 5, we experimented with five different settings: 256, 400, 512, 800, and 1024

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:36.441196Z

Source-reported events for the cited work

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Observation de07682c-87f8-4353-a6c1-e34fea5fdacb · outbound

This paper cites Lcoarse serves as the foundation of the model, while Lf ine and Lcujp further refine the unified representation space and enhance the model’s open-domain detection capabilities.

Open-set Cross Modal Generalization via Multimodal Unified Representation Lcoarse serves as the foundation of the model, while Lf ine and Lcujp further refine the unified representation space and enhance the model’s open-domain detection capabilities

Reference 63

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T15:48:36.199359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0ed9da58-6fc8-4401-ab6b-a4ca137ccec8 · outbound

This paper cites CUJP8, despite having more split block reorder- ing, optimizes memory usage and reduces training time compared to MMJP6 [14].

Open-set Cross Modal Generalization via Multimodal Unified Representation CUJP8, despite having more split block reorder- ing, optimizes memory usage and reduces training time compared to MMJP6 [14]

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:35.956451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4d271cca-30a9-434f-9f9a-a9835f3a91a5 · outbound

This paper cites The visualization maps audio-video-text triplets from the Valor32K dataset [7] into the unified rep- resentation space (codebook).

Open-set Cross Modal Generalization via Multimodal Unified Representation The visualization maps audio-video-text triplets from the Valor32K dataset [7] into the unified rep- resentation space (codebook)

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:48:35.616927Z

Source-reported events for the cited work

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Pith citing papers

Observation aa53c0d5-f2ba-4c21-9783-00fd73b7fa6f · inbound

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

TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal Open-set Cross Modal Generalization via Multimodal Unified Representation

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-05T21:53:34.172007Z

Source-reported events for the cited work

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