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Paper Citation Record · LEDGER

DreamWAM: Beyond RGB Future Prediction for World Action Models

As of 7 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 2026-08-06T06:34:29.942622+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=sha256:3ebe26c966fa4cd783bb81e7c4a874543aeec0caaabfbffca525160a5e61fabd

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=sha256:62bbe24b3d51f94f118f85d2d62a9c5a699559e168a2a05cafd225ccde2a580c

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=sha256:5259dacac4d132cdf68801df43693f31cc146e81869bebc6f98d6353ff554b19

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=sha256:842709500b0651c3c93d478564dbe38478a323f5185393ee3bbd6ac82506939d

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=sha256:560759a7b5e5558e699117330f753ed2e0c3a2f86530a3f1c62efc16dc2b7848

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:ddaecca8e55c7151877da5b453425c12f454b909d8c84a4b34e39b7c6cc26d74

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=sha256:85edacc7a75045d58879d4f3dec356c6b8b6dce55094ad5a7aa92b24799ce85f

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:e5bcb18017ad53679a421f146b7d1d0c7c26e4dbe48d81e87012c0313930654b

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=sha256:0de088eaf59f3b44ed040fcbca136ecec8ea8b5504527e83b0b7246e47d6c1b7

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:fceb09582d67be3ef9ee7e66a5654b2328abe27be59f6a1665ed8d783411e954

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=sha256:25d1828f7793d22be2194f85f936908302bf5f26ae4453638f61466d8fc0bdfa

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=sha256:8eb81f1fc3dd806c55b7eb1486f82cfeb37698ae0bc485ac8e18ad29b4d453d0

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:bbc2c2c545748e559af0de891540c9295dd8894c5b3d4647ae424aca8040106c

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=sha256:449587b2cc0d6947fd31b72688e5708853ef7c896bcf74eb6347b8bb320c261e

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=sha256:14816fef755f4bab5a432501f20b33df008ebe367ba1640cb99848fb6b2b2cfe

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=sha256:6570de98d5b7b82769a1330c2036e6742f9f55df03bf9aaeac9701eba1d917fa

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:ae2ab6d9500814570876ce0384cee9647c774acc75109de302b8460dd2677159

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=sha256:38cbca144448984407a5ff89bc628652f898a23952ce87a70c15f89b33019187

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=sha256:989ca8d074de290ea44553ea0f5db8c57f0d37f8bc52554138001f0e0b98282a

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=sha256:4928acff62722c29de7b80acac455cd56ee1c2425e5a34e10c15f461975a4db8

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=sha256:882c49602e928f82b79a304c1339db458e3f6f641c1ad0140d11a2337b7a021d

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:a01dcc01f9a4de737c78116b22efcd8cb63d8b70ee7c28877c7dd42acb222013

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:ae588320508f393b87c4f120707738fae0ad2e74d9d867582a8d989cf9204875

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:cb91a05a96967c74aac6fcb064842f1d5d5e6731bb77110a28fb3237de1fd451

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:c2657628f4e82a510d3a17f0f7313ff8e8479c4824d7adbeb9d9fb387a91c24f

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:d2357a2c47e1a7dd6d7c777c5070dff2f1d126fb591c40fbb7904771c0bec785

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=sha256:2d0442cbe00b958213cf983ecec30ea476a84b58a877670910a9978d38cc2d14

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:c6dfdb2fdc3f846e1e913d6e3a0b104686bbfaa0dba9efa4a700093f9b393084

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:e8df0c3c0b1c5fbda24be8aeb69676076f9db567f29e53e050aa0e5b00c8c9d7

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=sha256:002aab8f765d4ba7e783d0bca0c66c48a9dbf87c8b462b81db05d2a0f19518e3

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 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-08-06T11:59:28.007412Z digest=sha256:1629c236d790d821ab8c2ac4c434010f93268e2ae172a3df62632a1e88c1a9e3

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:f21760c0d5efe6fa3884e2a8a2e633b0ed80afc4db08f3e137ace4af4b32d71b

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=sha256:04d1baa0c284be0d91f0f3c1ca8a945529ff9a53122b9bac4e237dc44f3d1ae1

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:abb054a027e675e3c50f3ade4f6abc4d0150d23a48e774e33bbfe59115956b1b

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=sha256:21e7e72df7016a602aafc24ddb25b420c27fc0cbc0c6744d06132f41e1b98fb0

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=sha256:42812d39f28937843c32e7f9e94f731ee333029142fec8beb9726bbecb3c4098

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:be76062dcc7ba4f2103ba0a1d076d6931b4086de86355a59af2fa144740243aa

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=sha256:91f3bd2b0846b9703942b82c635a464954271be801abca8e1230c1295439725a

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:ea491e446ce7213695453986080a25afedcc90723b5da30a10a40571bd2986ad

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=sha256:1313d8dc7a0265892463c64ef8276802011cd166fae4a1d4504da1f39e25c48c

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=sha256:626c96d35df15a0c5581c315d5b54f1f926cd52a6d9269da898118148a66939f

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=sha256:915c77c158ec10aca961df0b393febf1acf6a3936dc98b910adc87b46746e16c

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=sha256:7c07784c17c4e3a0ccc8d0da7564dd06bc57562baf7670c1c62f832006b83b60

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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source=arxiv_source observed=2026-08-06T11:59:28.125004Z digest=sha256:261c64fe88ae32ceac7037fe221be318bb94cc801828545c2c05cbf6b3b64faa

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=sha256:3d7d0aa8a16a73d1c34b6d22841c657d6297dadf39ba692c2e1377426697a166

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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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T11:59:28.152150Z digest=sha256:83dd057bee7b97d2e06305253db94f816ea0f66459e3837aeced345924cbfabe

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:b5cd72863bcfd552ae64ad4a861745c2b769a26a92f3c35724ac808f827068a5

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=sha256:2c96f56d800c507bed7d879b1aecc29a2afcddbeb36760442f8ec314f5f9ed2f

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=sha256:83e98c3e03a68b21174b2dcbe0969b53c8c9ac01060b263e24466c531d98ec2c

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:ab519ecac7a1ea02139ca854b0ff717478d2fec3e042d1c24f9cb6e053a7e08c

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:e55cd3b732b8568bc78a623583a63f2926cdf5d3fc3b3185d69e9a12584b9add

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=sha256:26ec614fcfe624a413ae87661bd490a0fd235b33fbb359c9086d2f17184e5a2f

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=sha256:76f9a5c42e062398dd4d9aca0b310a2b70e391e90d20802473d60fe104073d42

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:a72ea1566604e5e084b78eb78e37f58c00ffcf65c087d5ba51c3527989e95a0a

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=sha256:7bfdf7e0885dcdc7e5f55fdfdc9eb6e411c33996acb033cc47e4b99e4018be9f

Pith citing papers

No inbound Pith citation observations are available.