Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:10:55.455485Z
Paper Citation Record · LEDGER
From Image to Video: An Empirical Study of Diffusion Representations
As of 16 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 2 inbound Pith citation observations for arXiv:2502.07001.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-19T03:42:54.620069Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T03:42:57.302590Z
Reference resolution
69 of 69 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 603821a0-9355-48c5-9aeb-a0481d66b0c7 · outbound
This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.
From Image to Video: An Empirical Study of Diffusion Representations Self-supervised learning from images with a joint-embedding predictive architecture
Reference 1
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Observation cf7f64f8-25c1-4c34-910c-da56a3c62b98 · outbound
This paper cites Video diffusion models learn the struc- ture of the dynamic world.
From Image to Video: An Empirical Study of Diffusion Representations Video diffusion models learn the struc- ture of the dynamic world
Reference 2
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Observation 84998fb5-9c41-4862-ad36-25ae68f7595f · outbound
This paper cites Learning by Reconstruction Produces Uninformative Features For Perception.
From Image to Video: An Empirical Study of Diffusion Representations Learning by Reconstruction Produces Uninformative Features For Perception
Reference 3
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Observation e8f2fc10-1067-4eb7-b442-9c176f7863b6 · outbound
This paper cites Label-efficient se- mantic segmentation with diffusion models.
From Image to Video: An Empirical Study of Diffusion Representations Label-efficient se- mantic segmentation with diffusion models
Reference 4
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Observation a21fbcaf-e472-4e30-a2ab-a570cd1ceb2a · outbound
This paper cites Revisiting Feature Prediction for Learning Visual Representations from Video.
From Image to Video: An Empirical Study of Diffusion Representations Revisiting Feature Prediction for Learning Visual Representations from Video
Reference 5
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Observation 65321793-a5fe-4987-8f30-8828dc9fc8d7 · outbound
This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.
From Image to Video: An Empirical Study of Diffusion Representations Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
Reference 6
- Resolution
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Source-reported events for the cited work
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Observation ae5814d3-b1c7-4258-a241-1b50a0120411 · outbound
This paper cites Deep regression on manifolds: a 3D rota- tion case study.
From Image to Video: An Empirical Study of Diffusion Representations Deep regression on manifolds: a 3D rota- tion case study
Reference 7
- Resolution
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Observation 2b88fef2-7f80-42e0-b5a4-fc00d09576d3 · outbound
This paper cites Emerg- ing properties in self-supervised vision transformers.
From Image to Video: An Empirical Study of Diffusion Representations Emerg- ing properties in self-supervised vision transformers
Reference 8
- Resolution
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Observation 2c952667-f4b4-437d-946e-a2045f6b52b9 · outbound
This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.
From Image to Video: An Empirical Study of Diffusion Representations Quo vadis, action recognition? a new model and the kinetics dataset
Reference 9
- Resolution
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Observation ddf9d714-8dfe-4364-b1e4-2a330064446e · outbound
This paper cites A Short Note on the Kinetics-700 Human Action Dataset.
From Image to Video: An Empirical Study of Diffusion Representations A Short Note on the Kinetics-700 Human Action Dataset
Reference 10
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Source-reported events for the cited work
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Observation 647ea506-fb21-412f-8709-191a86556497 · outbound
This paper cites Scaling 4D Representations.
From Image to Video: An Empirical Study of Diffusion Representations Scaling 4D Representations
Reference 11
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Source-reported events for the cited work
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Observation fd97b2ea-81ad-4ab1-84fb-bf8e4fc288ed · outbound
This paper cites an unresolved cited work.
From Image to Video: An Empirical Study of Diffusion Representations Unresolved cited work
Reference 12
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Observation 62146370-3bbb-4834-85ed-c1be60865c89 · outbound
This paper cites PaLI-3 Vision Language Models: Smaller, Faster, Stronger.
From Image to Video: An Empirical Study of Diffusion Representations PaLI-3 Vision Language Models: Smaller, Faster, Stronger
Reference 13
- Resolution
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Observation c7fff663-46f1-4cee-9c79-59e461514fc6 · outbound
This paper cites Text-to-image diffusion mod- els are zero shot classifiers.
From Image to Video: An Empirical Study of Diffusion Representations Text-to-image diffusion mod- els are zero shot classifiers
Reference 14
- Resolution
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Observation 6babfe3c-9302-4e56-9aee-1c71d713bea9 · outbound
This paper cites Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner.
From Image to Video: An Empirical Study of Diffusion Representations Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner
Reference 15
- Resolution
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Observation ceb7d32a-da1d-453d-bd88-0f0e747d5aa5 · outbound
This paper cites Depth map prediction from a single image using a multi-scale deep net- work.
From Image to Video: An Empirical Study of Diffusion Representations Depth map prediction from a single image using a multi-scale deep net- work
Reference 16
- Resolution
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Observation a71f2f6c-c156-4b51-a343-bf48d93d0515 · outbound
This paper cites Taming transformers for high-resolution image synthesis.
From Image to Video: An Empirical Study of Diffusion Representations Taming transformers for high-resolution image synthesis
Reference 17
- Resolution
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Source-reported events for the cited work
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Observation 48a5b6a2-1bea-47c0-9fda-cc34bcdc70fc · outbound
This paper cites Masked autoencoders as spatiotemporal learners.
From Image to Video: An Empirical Study of Diffusion Representations Masked autoencoders as spatiotemporal learners
Reference 18
- Resolution
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Observation ade7fd2f-118a-4d8b-a295-b245f66e7678 · outbound
This paper cites Diffusion Models and Representation Learning: A Survey.
From Image to Video: An Empirical Study of Diffusion Representations Diffusion Models and Representation Learning: A Survey
Reference 19
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Source-reported events for the cited work
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Observation 16a378de-c69e-41e8-8dcc-8909361ab035 · outbound
This paper cites Something Something.
From Image to Video: An Empirical Study of Diffusion Representations Something Something
Reference 20
- Resolution
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Source-reported events for the cited work
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Observation 20c8d60a-5b6a-427b-b8fd-cfcf907d1c47 · outbound
This paper cites Kubric: A scalable dataset generator.
From Image to Video: An Empirical Study of Diffusion Representations Kubric: A scalable dataset generator
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation 8d92fef7-1769-4742-b1e0-aeed694afa2b · outbound
This paper cites Photorealistic video generation with diffusion models.
From Image to Video: An Empirical Study of Diffusion Representations Photorealistic video generation with diffusion models
Reference 22
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Observation 7302ca0f-4509-4216-a41e-7b1fd9d63e17 · outbound
This paper cites Masked autoencoders are scalable vision learners.
From Image to Video: An Empirical Study of Diffusion Representations Masked autoencoders are scalable vision learners
Reference 23
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Observation 737ae461-0659-4691-a059-b1c40a504c27 · outbound
This paper cites Unsupervised keypoints from pretrained diffusion models.
From Image to Video: An Empirical Study of Diffusion Representations Unsupervised keypoints from pretrained diffusion models
Reference 24
- Resolution
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Source-reported events for the cited work
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Observation a2be131a-35d6-40b5-873b-dd347fdbb184 · outbound
This paper cites Denoising diffu- sion probabilistic models.
From Image to Video: An Empirical Study of Diffusion Representations Denoising diffu- sion probabilistic models
Reference 25
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Source-reported events for the cited work
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Observation a32fe247-85c8-4dc7-8b9e-4ab376ec1002 · outbound
This paper cites DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos.
From Image to Video: An Empirical Study of Diffusion Representations DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos
Reference 26
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Source-reported events for the cited work
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Observation 68812302-5910-4492-ada0-0d5cf32723e1 · outbound
This paper cites Elucidating the design space of diffusion-based generative models.
From Image to Video: An Empirical Study of Diffusion Representations Elucidating the design space of diffusion-based generative models
Reference 27
- Resolution
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Source-reported events for the cited work
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Observation 87a222f0-25fc-41b2-bad7-3d32451b08f8 · outbound
This paper cites Your diffusion model is secretly a zero-shot classifier.
From Image to Video: An Empirical Study of Diffusion Representations Your diffusion model is secretly a zero-shot classifier
Reference 28
- Resolution
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Observation c3a21647-dd1e-4432-8077-36b0cb0d8030 · outbound
This paper cites Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models.
From Image to Video: An Empirical Study of Diffusion Representations Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
Reference 29
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Source-reported events for the cited work
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This paper cites Diffusion hyperfeatures: Search- ing through time and space for semantic correspondence.
From Image to Video: An Empirical Study of Diffusion Representations Diffusion hyperfeatures: Search- ing through time and space for semantic correspondence
Reference 30
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This paper cites Understanding deep image representations by inverting them.
From Image to Video: An Empirical Study of Diffusion Representations Understanding deep image representations by inverting them
Reference 31
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Observation f6c3539d-ca5e-4a6c-b193-e525ed96fc62 · outbound
This paper cites Lexicon3d: Probing vi- sual foundation models for complex 3d scene understanding.
From Image to Video: An Empirical Study of Diffusion Representations Lexicon3d: Probing vi- sual foundation models for complex 3d scene understanding
Reference 32
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Observation 24f582d3-87f7-4921-a4c4-d2b6ba373ad6 · outbound
This paper cites NeRF: Representing scenes as neural radiance fields for view syn- thesis.
From Image to Video: An Empirical Study of Diffusion Representations NeRF: Representing scenes as neural radiance fields for view syn- thesis
Reference 33
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From Image to Video: An Empirical Study of Diffusion Representations Diffusion Models Beat GANs on Image Classification
Reference 34
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From Image to Video: An Empirical Study of Diffusion Representations DiffTAD: Temporal action detection with proposal denoising diffusion
Reference 35
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From Image to Video: An Empirical Study of Diffusion Representations Unresolved cited work
Reference 36
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This paper cites Self-supervised video pretraining yields robust and more human-aligned visual representations.
From Image to Video: An Empirical Study of Diffusion Representations Self-supervised video pretraining yields robust and more human-aligned visual representations
Reference 37
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This paper cites Per- ception Test: A diagnostic benchmark for multimodal video models.
From Image to Video: An Empirical Study of Diffusion Representations Per- ception Test: A diagnostic benchmark for multimodal video models
Reference 38
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From Image to Video: An Empirical Study of Diffusion Representations Scalable diffusion models with transformers
Reference 39
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From Image to Video: An Empirical Study of Diffusion Representations The 2017 DAVIS Challenge on Video Object Segmentation
Reference 40
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From Image to Video: An Empirical Study of Diffusion Representations Learn- ing transferable visual models from natural language super- vision
Reference 41
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From Image to Video: An Empirical Study of Diffusion Representations High-resolution image syn- thesis with latent diffusion models
Reference 42
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Source-reported events for the cited work
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From Image to Video: An Empirical Study of Diffusion Representations U- Net: Convolutional networks for biomedical image segmen- tation
Reference 43
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Observation dbfba91e-e117-43b3-a687-098d0627e39b · outbound
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From Image to Video: An Empirical Study of Diffusion Representations Berg, and Li Fei-Fei
Reference 44
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From Image to Video: An Empirical Study of Diffusion Representations Scene representation transformer: Geometry-free novel view syn- thesis through set-latent scene representations
Reference 45
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Observation 3b8c6641-290a-4a7d-8e5b-11179bae4712 · outbound
This paper cites Only time can tell: Discovering temporal data for temporal modeling.
From Image to Video: An Empirical Study of Diffusion Representations Only time can tell: Discovering temporal data for temporal modeling
Reference 46
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Observation 6fb7003e-13f5-43c8-bb60-fff423a83da4 · outbound
This paper cites MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model.
From Image to Video: An Empirical Study of Diffusion Representations MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model
Reference 47
- Resolution
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Observation f154804d-1108-4532-90cb-1f8bf6e6e25a · outbound
This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.
From Image to Video: An Empirical Study of Diffusion Representations Deep unsupervised learning using nonequilibrium thermodynamics
Reference 48
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Observation 7b302f72-d9ab-45a3-bb7e-53a11f481eb2 · outbound
This paper cites Scalability in perception for autonomous driving: Waymo Open Dataset.
From Image to Video: An Empirical Study of Diffusion Representations Scalability in perception for autonomous driving: Waymo Open Dataset
Reference 49
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Source-reported events for the cited work
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Observation 23f0ce83-05b5-4ff3-bb97-8c14bd76ba9e · outbound
This paper cites Emergent correspondence from image diffusion.
From Image to Video: An Empirical Study of Diffusion Representations Emergent correspondence from image diffusion
Reference 50
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Source-reported events for the cited work
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Observation ea064e57-1183-4773-92f6-55510f4c043b · outbound
This paper cites VideoMAE: Masked autoencoders are data-efficient learners for self-supervised video pre-training.
From Image to Video: An Empirical Study of Diffusion Representations VideoMAE: Masked autoencoders are data-efficient learners for self-supervised video pre-training
Reference 51
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2ffa4df1-3728-42d1-89f9-fbbfc6e56103 · outbound
This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.
From Image to Video: An Empirical Study of Diffusion Representations Towards Accurate Generative Models of Video: A New Metric & Challenges
Reference 52
- Resolution
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Source-reported events for the cited work
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Observation 94445917-140d-4ed1-83c5-d54ac64332f1 · outbound
This paper cites Neural discrete representation learning.
From Image to Video: An Empirical Study of Diffusion Representations Neural discrete representation learning
Reference 53
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 958500c9-b3bb-4d5f-9c02-e736c5693d7a · outbound
This paper cites The iNaturalist species classification and detection dataset.
From Image to Video: An Empirical Study of Diffusion Representations The iNaturalist species classification and detection dataset
Reference 54
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation af177f6d-7537-46b7-923d-127918f55d41 · outbound
This paper cites Hudson, Thomas Albert Keck, Joao Carreira, Alexey Doso- vitskiy, Mehdi S.
From Image to Video: An Empirical Study of Diffusion Representations Hudson, Thomas Albert Keck, Joao Carreira, Alexey Doso- vitskiy, Mehdi S
Reference 55
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3c76d85f-a3a4-41f4-b74a-885ad9d09450 · outbound
This paper cites Attention is all you need.
From Image to Video: An Empirical Study of Diffusion Representations Attention is all you need
Reference 56
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7502c86a-a9a9-438b-82d0-d8af2e1c7a85 · outbound
This paper cites VideoMAE v2: Scaling video masked autoencoders with dual masking.
From Image to Video: An Empirical Study of Diffusion Representations VideoMAE v2: Scaling video masked autoencoders with dual masking
Reference 57
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2f9ede65-af59-4efc-aee6-1dbd688e7143 · outbound
This paper cites Controlling Space and Time with Diffusion Models.
From Image to Video: An Empirical Study of Diffusion Representations Controlling Space and Time with Diffusion Models
Reference 58
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0fe87e0a-d124-4519-87a1-eba6c744e2ac · outbound
This paper cites Denoising diffusion autoencoders are unified self-supervised learners.
From Image to Video: An Empirical Study of Diffusion Representations Denoising diffusion autoencoders are unified self-supervised learners
Reference 59
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a6a4e390-b173-415c-9063-ac78ec4bac71 · outbound
This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.
From Image to Video: An Empirical Study of Diffusion Representations Open-vocabulary panop- tic segmentation with text-to-image diffusion models
Reference 60
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 27edcb1a-eb8b-4d72-8352-ff598a435d7b · outbound
This paper cites Diffusion Model as Rep- resentation Learner.
From Image to Video: An Empirical Study of Diffusion Representations Diffusion Model as Rep- resentation Learner
Reference 61
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b0ac0337-c4a8-47d4-ba5a-16d07178cb95 · outbound
This paper cites Gundavarapu, Luca Ver- sari, Kihyuk Sohn, David Minnen, Yong Cheng, Vigh- nesh Birodkar, Agrim Gupta, Xiuye Gu, Alexander G.
From Image to Video: An Empirical Study of Diffusion Representations Gundavarapu, Luca Ver- sari, Kihyuk Sohn, David Minnen, Yong Cheng, Vigh- nesh Birodkar, Agrim Gupta, Xiuye Gu, Alexander G
Reference 62
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation af5a3197-f2c1-4c5a-901f-b84be0514da7 · outbound
This paper cites A tale of two features: Stable diffusion complements DINO for zero-shot semantic correspondence.
From Image to Video: An Empirical Study of Diffusion Representations A tale of two features: Stable diffusion complements DINO for zero-shot semantic correspondence
Reference 63
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation adc973b1-8a9f-4c9f-810d-c9d4f59e998a · outbound
This paper cites A Survey of Diffusion Based Image Generation Models: Issues and Their Solutions.
From Image to Video: An Empirical Study of Diffusion Representations A Survey of Diffusion Based Image Generation Models: Issues and Their Solutions
Reference 64
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54c34bff-d2ce-477f-8bfd-a6ac1a5c169a · outbound
This paper cites an unresolved cited work.
From Image to Video: An Empirical Study of Diffusion Representations Unresolved cited work
Reference 65
- Resolution
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- raw_fallback, observed 2026-08-08T14:10:55.793939Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1462df58-ed28-4474-a511-dcab881afb14 · outbound
This paper cites Unleashing text-to-image diffusion models for visual perception.
From Image to Video: An Empirical Study of Diffusion Representations Unleashing text-to-image diffusion models for visual perception
Reference 66
- Resolution
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Source-reported events for the cited work
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Observation 0f76226c-d04b-4335-801b-81acca099df6 · outbound
This paper cites Places: A 10 million image database for scene recognition.
From Image to Video: An Empirical Study of Diffusion Representations Places: A 10 million image database for scene recognition
Reference 67
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3b551034-2701-48cf-a3d5-164bf2b1f3d6 · outbound
This paper cites Stereo magnification: Learning view syn- thesis using multiplane images.
From Image to Video: An Empirical Study of Diffusion Representations Stereo magnification: Learning view syn- thesis using multiplane images
Reference 68
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6e333442-b790-49a6-871e-4f4bcf9c06e7 · outbound
This paper cites Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation.
From Image to Video: An Empirical Study of Diffusion Representations Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation
Reference 69
- Resolution
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Source-reported events for the cited work
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Pith citing papers
Observation a2d5ddbd-90f3-4119-9328-a330dd5eaf9c · inbound
Frozen Forecasting: A Unified Evaluation cites this paper.
Frozen Forecasting: A Unified Evaluation From Image to Video: An Empirical Study of Diffusion Representations
Reference 41
- Resolution
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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0b36fdbc-3921-4f57-8d81-c211e5d371ff · inbound
Video Generation with Predictive Latents cites this paper.
Video Generation with Predictive Latents From Image to Video: An Empirical Study of Diffusion Representations
Reference 48
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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.