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Paper Citation Record · LEDGER

DreamWAM: Beyond RGB Future Prediction for World Action Models

As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2608.04996.

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

pith.paper-citation-record.v1
2608.04996 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:59:28.176050Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

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

measured 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

55 of 55 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved52
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 349b7474-1876-4536-813b-ba85cdef8772 · outbound

This paper cites Fast-WAM: Do World Action Models Need Test-time Future Imagination?.

DreamWAM: Beyond RGB Future Prediction for World Action Models Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 1

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source=arxiv_source observed=2026-08-06T11:59:27.924099Z digest=sha256:6787019d77825f6586a9dbb4396a7f4801f81d35d222d1bd0dd9083cfc4783c1

Observation 6e8d2c42-dac2-42f6-84e5-dd34194ec02e · outbound

This paper cites WorldVLA: Towards Autoregressive Action World Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models WorldVLA: Towards Autoregressive Action World Model

Reference 2

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source=arxiv_source observed=2026-08-06T11:59:27.927472Z digest=sha256:e9e8a625684d86fe499f6313954b0046871c1734492392d60514cfe29df01be1

Observation fec478f5-1874-4055-9d9d-12a6b8206766 · outbound

This paper cites Motus: A Unified Latent Action World Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models Motus: A Unified Latent Action World Model

Reference 3

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source=arxiv_source observed=2026-08-06T11:59:27.930502Z digest=sha256:abe22cab53667f75d1054d7a510e5b7c96d98da32c6ae187ef9b9ea6ea0385b8

Observation eb3d5f58-2c8a-43b0-a17d-7433f50e1fcf · outbound

This paper cites Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising.

DreamWAM: Beyond RGB Future Prediction for World Action Models Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

Reference 4

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source=arxiv_source observed=2026-08-06T11:59:27.933466Z digest=sha256:139ec244796054a52683969c8ba659ce56d5958d53821c2b2661ad0d1615552b

Observation 0722d4c7-d541-490d-b5ec-1b42ebd2c7d2 · outbound

This paper cites Causal World Modeling for Robot Control.

DreamWAM: Beyond RGB Future Prediction for World Action Models Causal World Modeling for Robot Control

Reference 5

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source=arxiv_source observed=2026-08-06T11:59:27.936287Z digest=sha256:08a0fac31e3bca765f404065c7c8f53e6d85ab1d773b7f7dc9e224fc69478aa1

Observation ea8658ba-0d32-45b6-871b-340b39faf206 · outbound

This paper cites GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch.

DreamWAM: Beyond RGB Future Prediction for World Action Models GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

Reference 6

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source=arxiv_source observed=2026-08-06T11:59:27.939168Z digest=sha256:e0fac65ff5806415f8338d8bcd230d0bd95b20d8245abf70c8751d747ce49066

Observation 1a27b0d6-d3e0-4dd7-8b07-5584615e6f89 · outbound

This paper cites DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving.

DreamWAM: Beyond RGB Future Prediction for World Action Models DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving

Reference 7

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source=arxiv_source observed=2026-08-06T11:59:27.942236Z digest=sha256:2bfbf10fd74754d4848ecd13df282f7c23e3e4cf19810428b6a067487acb3b91

Observation 269cff1d-a1e9-4105-a3ff-0a569633c658 · outbound

This paper cites SANA-WM: Efficient Minute-Scale World Modeling with Hybrid Linear Diffusion Transformer.

DreamWAM: Beyond RGB Future Prediction for World Action Models SANA-WM: Efficient Minute-Scale World Modeling with Hybrid Linear Diffusion Transformer

Reference 8

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source=arxiv_source observed=2026-08-06T11:59:27.945324Z digest=sha256:5223980758be2f66ed91ca4a45d6355c67862e2e31400da262ba3311424176d7

Observation ae0b8ad0-fb38-4fb3-b6bb-65d5f1650054 · outbound

This paper cites Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets.

DreamWAM: Beyond RGB Future Prediction for World Action Models Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets

Reference 9

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source=arxiv_source observed=2026-08-06T11:59:27.948270Z digest=sha256:fd3f0fe03992e08a525e769c47d9d0da88b93c2f2fbf1bf1fcd0ca13f342e15a

Observation df4479c5-7d5d-4a12-88db-728569ebce45 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 10

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T11:59:27.950873Z digest=sha256:6bc6002cf652324ba37d9252cadd1e86f47e4370067551e202f04d3db59c4a90

Observation 59b4ad76-093b-48eb-b39d-37f94da3fc6a · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

DreamWAM: Beyond RGB Future Prediction for World Action Models RT-1: Robotics Transformer for Real-World Control at Scale

Reference 11

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source=arxiv_source observed=2026-08-06T11:59:27.953650Z digest=sha256:75427cc15f2cf8eea915c615391d05ac6f1243b9cb38cfa06cee74ff1461b99a

Observation 14732903-8965-4091-af54-ec7025440a39 · outbound

This paper cites Conference on Robot Learning , pages=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Conference on Robot Learning , pages=

Reference 12

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source=arxiv_source observed=2026-08-06T11:59:27.956241Z digest=sha256:cc406d651e7d3b9b5f274f6bea130f07e39f0a59c9e400e8835375ab308a7ebf

Observation 4b3f5218-7955-4474-a9d0-1e53ad0f7ecd · outbound

This paper cites Octo: An Open-Source Generalist Robot Policy.

DreamWAM: Beyond RGB Future Prediction for World Action Models Octo: An Open-Source Generalist Robot Policy

Reference 13

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source=arxiv_source observed=2026-08-06T11:59:27.959101Z digest=sha256:eab2f22504decda333ef8f3409001070136478c6bd2df9b4d097d0a655a2a98f

Observation adcfcf02-2550-4722-a62f-cc67bd48f804 · outbound

This paper cites MotionVLA: Injecting Geometric Motion into Vision-Language-Action Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models MotionVLA: Injecting Geometric Motion into Vision-Language-Action Model

Reference 14

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source=arxiv_source observed=2026-08-06T11:59:27.961726Z digest=sha256:8ec43cae5ac053f91df679e07431e2eaa8cbb5d473bd28f767aff11e801f029a

Observation 73950fe1-e968-4c05-9e45-eef486247fac · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models OpenVLA: An Open-Source Vision-Language-Action Model

Reference 15

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source=arxiv_source observed=2026-08-06T11:59:27.964281Z digest=sha256:3aa237e7fbc8bb6f5af1113e5a90d4dbdb5579a560aa4fbf92d8a688d619f829

Observation 9ba2c97c-e9d4-44f2-b974-c29ac515e912 · outbound

This paper cites UniVLA: Learning to Act Anywhere with Task-centric Latent Actions.

DreamWAM: Beyond RGB Future Prediction for World Action Models UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

Reference 16

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source=arxiv_source observed=2026-08-06T11:59:27.967191Z digest=sha256:e949f346d8910cdc2659033bcc77c2212938a4cd5f0e77639709a5350a8aa16a

Observation 9b711223-87c9-4bae-9f09-7f83e531a248 · outbound

This paper cites Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success.

DreamWAM: Beyond RGB Future Prediction for World Action Models Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 17

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source=arxiv_source observed=2026-08-06T11:59:27.970489Z digest=sha256:76ad5dc4181a3edfb6e4692f36a028af6b82aaa31607fc78799a8044c66ff68d

Observation 53e87fca-9d14-4fe3-bb27-f5f644b4389c · outbound

This paper cites an unresolved cited work.

DreamWAM: Beyond RGB Future Prediction for World Action Models Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-08-06T11:59:27.973862Z digest=sha256:cd130fa7bde451c529bcc9e940a5e064aec8c5789f5f6b71bac7d207929b549d

Observation 39f5e92a-024e-4ebc-a675-34fc6eb99b67 · outbound

This paper cites $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization.

DreamWAM: Beyond RGB Future Prediction for World Action Models $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 19

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source=arxiv_source observed=2026-08-06T11:59:27.976432Z digest=sha256:884707b01633afd032c81050d88c0ef5fe3eef1577461902ed5c09719ff03587

Observation 9729b5b0-2eca-403c-96f6-add7f6347aa3 · outbound

This paper cites FAST: Efficient Action Tokenization for Vision-Language-Action Models.

DreamWAM: Beyond RGB Future Prediction for World Action Models FAST: Efficient Action Tokenization for Vision-Language-Action Models

Reference 20

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source=arxiv_source observed=2026-08-06T11:59:27.979101Z digest=sha256:0eed18c52d14f1416f97b6e28d796c22591036a202f76f35841cdf147dbd80ee

Observation 42acc6e8-6e7f-456c-9f23-55e914b75a56 · outbound

This paper cites an unresolved cited work.

DreamWAM: Beyond RGB Future Prediction for World Action Models Unresolved cited work

Reference 21

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source=arxiv_source observed=2026-08-06T11:59:27.981801Z digest=sha256:e891f74b37017bb7ca8ffe0e86e0da86a18c84f5fa8ec102e3009a9edcb557cd

Observation af806737-ffc3-4880-8aa8-b710d4bd60a7 · outbound

This paper cites ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities.

DreamWAM: Beyond RGB Future Prediction for World Action Models ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

Reference 22

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source=arxiv_source observed=2026-08-06T11:59:27.984035Z digest=sha256:68c8edf1fbc4ae5d04d79f96c465888dbf0669d41d0e0cd37fdd89fb07b37b98

Observation 072362db-483e-4a48-8ab8-537d395b2911 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Advances in Neural Information Processing Systems , volume=

Reference 23

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source=arxiv_source observed=2026-08-06T11:59:27.986976Z digest=sha256:4a9a54441e7953774509991da72b9944f174976910d971bbcfb23751cef4b9b5

Observation 03a5a5af-0db4-41eb-9e59-25ca39606d81 · outbound

This paper cites arXiv preprint arXiv:2510.12276 , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models arXiv preprint arXiv:2510.12276 , year=

Reference 24

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source=arxiv_source observed=2026-08-06T11:59:27.989250Z digest=sha256:0f718c29ee5094d7c124dc60d3ad187c98b40a17e43433c4c6d0d809e5b069a5

Observation 08eb154b-0347-41fc-a166-9131af9607f0 · outbound

This paper cites arXiv preprint arXiv:2510.13375 , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models arXiv preprint arXiv:2510.13375 , year=

Reference 25

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source=arxiv_source observed=2026-08-06T11:59:27.991808Z digest=sha256:08412473718cc85d49d36eb8e26a18bff1134d982383bfaac752da57913a0e10

Observation 4ea46a74-9f7c-4254-bac6-08496d862c2e · outbound

This paper cites SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model

Reference 26

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source=arxiv_source observed=2026-08-06T11:59:27.994101Z digest=sha256:0fc5a4531366577e9827f93191f21e8ec18698f2990f8a4dc57952081845859a

Observation b7df52d0-2bea-422c-a38b-49f06c97be77 · outbound

This paper cites GeoVLA: Empowering 3D Representations in Vision-Language-Action Models.

DreamWAM: Beyond RGB Future Prediction for World Action Models GeoVLA: Empowering 3D Representations in Vision-Language-Action Models

Reference 27

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source=arxiv_source observed=2026-08-06T11:59:27.996941Z digest=sha256:bce44dfa5d62f414dc87f3583b9e14824ce4b6c0da30e835789c24eefb6a2511

Observation 57806a0b-41ab-45b6-b2e6-1988f0581f96 · outbound

This paper cites IEEE Robotics and Automation Letters , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models IEEE Robotics and Automation Letters , volume=

Reference 28

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source=arxiv_source observed=2026-08-06T11:59:27.999582Z digest=sha256:dd63430c00094cdc201fcddf7771802180dcdfdc18bcad2edd5f9f279dd73b77

Observation 223409be-ab1b-4df8-bd83-558fa86b442e · outbound

This paper cites arXiv preprint arXiv:2603.00466 , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models arXiv preprint arXiv:2603.00466 , year=

Reference 29

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source=arxiv_source observed=2026-08-06T11:59:28.002431Z digest=sha256:95b8389b7efd35ad7a96e8071ef7647a98a775169477351427e7f8d7ed569172

Observation be199bd7-a337-4f11-a865-fa77c59a3271 · outbound

This paper cites VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models.

DreamWAM: Beyond RGB Future Prediction for World Action Models VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models

Reference 30

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source=arxiv_source observed=2026-08-06T11:59:28.004817Z digest=sha256:230b6f59c3323c64abe6a58f818bc08d25728b917c80234da87b1537f0b529f6

Observation 1c4f71fc-aed3-40ff-a03b-ed21882b5310 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Advances in Neural Information Processing Systems , volume=

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T11:59:28.007412Z digest=sha256:4b09aaf5f713c43dc3301461fd0cfc4c6480db7789c0af7354b13200933cc362

Observation 8c6ddd3a-5b50-4750-89d6-9c3a0c2dd22a · outbound

This paper cites World Action Models are Zero-shot Policies.

DreamWAM: Beyond RGB Future Prediction for World Action Models World Action Models are Zero-shot Policies

Reference 32

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source=arxiv_source observed=2026-08-06T11:59:28.009695Z digest=sha256:5e4c0a46255097c2c58e77646d82257e85e58ff2d11fc3afb00aef4e2b016c30

Observation f9c1168e-e63f-4e71-aa67-19ff84f54f2d · outbound

This paper cites Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning.

DreamWAM: Beyond RGB Future Prediction for World Action Models Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 33

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source=arxiv_source observed=2026-08-06T11:59:28.012388Z digest=sha256:535518f4083890a9ef4122d898e24aacbc032ea442ac9955fdba5b72e86a43dd

Observation fe49fbe1-1e27-442a-92a0-79f3131c52e7 · outbound

This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.

DreamWAM: Beyond RGB Future Prediction for World Action Models GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 34

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source=arxiv_source observed=2026-08-06T11:59:28.014913Z digest=sha256:e126964dcac4c4a1d0c763d969abc19ced3990bdd349578118afcbd839b3a1d3

Observation fc6cf896-24bf-48e7-8994-dbd725c8a5c8 · outbound

This paper cites X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

Reference 35

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source=arxiv_source observed=2026-08-06T11:59:28.017508Z digest=sha256:494ebc3b35833cc5f7a1bbfb2e0f6f4982fd27eddad023db75f76fec68bb5154

Observation 64c93299-25a2-4bfe-a77d-25c04149d9ea · outbound

This paper cites arXiv preprint arXiv:2601.03782 , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models arXiv preprint arXiv:2601.03782 , year=

Reference 36

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source=arxiv_source observed=2026-08-06T11:59:28.020106Z digest=sha256:0e4737699215e30b86e3cc89248012be5ff76f11cbdf11020f02db4a552e59f5

Observation 7b4da607-f483-49d6-a7e4-e5a12f5a7e77 · outbound

This paper cites CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation.

DreamWAM: Beyond RGB Future Prediction for World Action Models CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation

Reference 37

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source=arxiv_source observed=2026-08-06T11:59:28.022493Z digest=sha256:e97a81a2292bad3ef25aef0693ca6654400b255dcd143ce783c77b18899deac5

Observation f01ce99b-c333-4dcf-ab35-c2465cfd93c7 · outbound

This paper cites SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics.

DreamWAM: Beyond RGB Future Prediction for World Action Models SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics

Reference 38

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source=arxiv_source observed=2026-08-06T11:59:28.025058Z digest=sha256:431a36fa6a703e2a589ee698839ca44f2d1a3dbbb7b063ce29ef66395705d7f8

Observation cf1e7798-3028-4b35-a0a6-2222088f264d · outbound

This paper cites arXiv preprint arXiv:2602.09849 , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models arXiv preprint arXiv:2602.09849 , year=

Reference 39

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T11:59:28.029136Z digest=sha256:f27f0939514768ead26e7fb8f8af7945e76a667d5891ad616a0f2ca94f298c51

Observation 3758e7fa-53e6-43e5-a358-87b44c92efc1 · outbound

This paper cites A Pragmatic VLA Foundation Model.

DreamWAM: Beyond RGB Future Prediction for World Action Models A Pragmatic VLA Foundation Model

Reference 40

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source=arxiv_source observed=2026-08-06T11:59:28.043138Z digest=sha256:1887aaf4fac87b73b1104b943ec38f79fbb1e2db1235bc707fd34a74c1a6dd7a

Observation 88d19478-b5a7-4704-b011-577faf117883 · outbound

This paper cites Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments.

DreamWAM: Beyond RGB Future Prediction for World Action Models Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Reference 41

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no resolver link, observed 2026-08-06T11:59:28.066566Z

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source=arxiv_source observed=2026-08-06T11:59:28.066566Z digest=sha256:d3837a49d4254be776dbb06e7eb5989d9700183bbf4602dd5c11cef1f3c21abf

Observation 37fbf687-49ca-42e5-8ed6-cfd99f906024 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 42

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source=arxiv_source observed=2026-08-06T11:59:28.086599Z digest=sha256:53d211b7b4acdfe8ff61c4ccbafea19a4126bf33ed33d9e42ce7e7e08782d567

Observation 2960e5b1-ccbf-466f-bc41-33d78c3e3f3b · outbound

This paper cites Advances in neural information processing systems , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Advances in neural information processing systems , volume=

Reference 43

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no resolver link, observed 2026-08-06T11:59:28.104136Z

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source=arxiv_source observed=2026-08-06T11:59:28.104136Z digest=sha256:bc6f89b1a83fdda450721a3b5d7b9e03d0a489fc8324ccc6514422a598f3ef0b

Observation 76ba7be3-3e53-48ec-b549-ab3c1a06c5d7 · outbound

This paper cites arXiv preprint arXiv:2602.10098 , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models arXiv preprint arXiv:2602.10098 , year=

Reference 44

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no resolver link, observed 2026-08-06T11:59:28.125004Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T11:59:28.125004Z digest=sha256:6ed583577cf0a7bf93e9d1d1222c61e0d9e2468f44f67a2daa1934fbe4e22c75

Observation 5d39e72b-a378-4806-8d20-5d7c82034cbb · outbound

This paper cites World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems.

DreamWAM: Beyond RGB Future Prediction for World Action Models World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems

Reference 45

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no resolver link, observed 2026-08-06T11:59:28.149079Z

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source=arxiv_source observed=2026-08-06T11:59:28.149079Z digest=sha256:4a0e7f4ce9f07183d376316719d36624b7dce8afbae0b15344059abcf003020e

Observation eb4d346e-90e1-4e38-a40c-0d1ef87de334 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Advances in Neural Information Processing Systems , volume=

Reference 46

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no resolver link, observed 2026-08-06T11:59:28.152150Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T11:59:28.152150Z digest=sha256:6ab77f2b4cd9b7688347cc65403258f5bc5c60573548ff78d397b8d8d713c628

Observation 4ebf7cc6-55e8-421d-a150-095661edff97 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Advances in Neural Information Processing Systems , volume=

Reference 47

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T11:59:28.154987Z digest=sha256:5bde31fbcbb1a9ea25bae0f58890e7a2d4441810a4bfc238d99f45060aacad0e

Observation eb41739a-d234-4028-8f48-4db5a6afbf19 · outbound

This paper cites LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models.

DreamWAM: Beyond RGB Future Prediction for World Action Models LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models

Reference 48

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source=arxiv_source observed=2026-08-06T11:59:28.157857Z digest=sha256:bf858ea4ebb4fa178070bc3adc15bc384c6fea08934b0697bbba2ef70340f8a5

Observation af9beb80-efb9-492a-9953-9f36e54bfc84 · outbound

This paper cites European conference on computer vision , pages=.

DreamWAM: Beyond RGB Future Prediction for World Action Models European conference on computer vision , pages=

Reference 49

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source=arxiv_source observed=2026-08-06T11:59:28.160748Z digest=sha256:173e44c60efa3f0cc664912e87c25ace73c356fa482d2fdc8db769cc468cf2a8

Observation 4a3c2dbd-3c38-419a-bda3-49aa3dc3fd26 · outbound

This paper cites Transactions on Machine Learning Research Journal , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models Transactions on Machine Learning Research Journal , year=

Reference 50

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source=arxiv_source observed=2026-08-06T11:59:28.163583Z digest=sha256:30cfe920953bfa088984d4b1a06bad6f512607ffa59b62dc08c481f32d54ea43

Observation 52ba659b-23b2-49e4-b54c-353e1c66ae3a · outbound

This paper cites Depth Anything 3: Recovering the Visual Space from Any Views.

DreamWAM: Beyond RGB Future Prediction for World Action Models Depth Anything 3: Recovering the Visual Space from Any Views

Reference 51

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source=arxiv_source observed=2026-08-06T11:59:28.166186Z digest=sha256:e265dae779453a6350eab59d388652d3cf899af7f7c9b8de20332d51a09bdb93

Observation d15f438c-0c1c-4847-909f-3db010846170 · outbound

This paper cites The eleventh international conference on learning representations , year=.

DreamWAM: Beyond RGB Future Prediction for World Action Models The eleventh international conference on learning representations , year=

Reference 52

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source=arxiv_source observed=2026-08-06T11:59:28.168957Z digest=sha256:59d0102a6edea9dcb564bf772e24a176e610fe52f2e04b33855b683823439e31

Observation a253e39f-5123-439d-a0a1-9739baa2c4a4 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

DreamWAM: Beyond RGB Future Prediction for World Action Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 53

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source=arxiv_source observed=2026-08-06T11:59:28.171196Z digest=sha256:dd8d087cb1d0ff3554906b5175fde4f47f00c575ec59023801c1c99a70ee336a

Observation 85c10b39-ce12-4265-befc-e66b0d208e0b · outbound

This paper cites Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think.

DreamWAM: Beyond RGB Future Prediction for World Action Models Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Reference 54

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source=arxiv_source observed=2026-08-06T11:59:28.173683Z digest=sha256:2424f601807ae524504dccecf68b4b396ff02ded9b20f292b86f28bffbf72738

Observation d06083b8-33cf-4736-8761-04016e175472 · outbound

This paper cites generation: Taming optimization dilemma in latent diffusion models , author=.

DreamWAM: Beyond RGB Future Prediction for World Action Models generation: Taming optimization dilemma in latent diffusion models , author=

Reference 55

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source=arxiv_source observed=2026-08-06T11:59:28.176050Z digest=sha256:2a98aa7bf97f16c6d708f9d80cff5c927bd3d054b4db46f5cfde70708f113043

Pith citing papers

No inbound Pith citation observations are available.