Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models | Paper Citation Record

Observation b4656ede-f50d-4899-a5a7-de2b408c1173 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 1

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Observation 1222e5b5-f207-49a1-962f-fc8c8e1bc8ee · outbound

This paper cites How learning by reconstruction produces uninformative features for perception.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models How learning by reconstruction produces uninformative features for perception

Reference 2

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Observation 7c434683-3031-45da-8088-35bcbdaf261e · outbound

This paper cites Motus: A unified latent action world model.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Motus: A unified latent action world model

Reference 3

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Observation 861da261-3035-4b17-84c9-1b2650790329 · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 4

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Observation 02c89345-bc2d-4519-9f3a-8bb185f4ea93 · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 5

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Observation 228d84d0-e82f-4430-9d22-2fbfd362cb2d · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

Reference 6

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Observation 5fc537c6-01e6-4577-97df-18a21e9aafa0 · outbound

This paper cites WorldVLA: Towards Autoregressive Action World Model.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models WorldVLA: Towards Autoregressive Action World Model

Reference 7

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Observation be67d509-98b8-48b2-9a6d-ce3413b2d76b · outbound

This paper cites GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation

Reference 8

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Observation b807ea57-1fec-4a61-8274-dfefb84668f1 · outbound

This paper cites Lawam: Latent world action models for efficient dynamics-aware robot policies.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Lawam: Latent world action models for efficient dynamics-aware robot policies

Reference 9

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Observation bbde95d9-ecfe-43f0-b393-07365fed4b99 · outbound

This paper cites RoboTwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models RoboTwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation

Reference 10

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Observation 34c671af-598d-434b-b0a0-55d3d5239725 · outbound

This paper cites Learning Universal Policies via Text-Guided Video Generation.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Learning Universal Policies via Text-Guided Video Generation

Reference 11

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Observation 1a6b8785-226e-4feb-86a5-441be26e6a87 · outbound

This paper cites LIBERO-Plus : A progressive robustness benchmark for visual-language-action models.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models LIBERO-Plus : A progressive robustness benchmark for visual-language-action models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:47.973666Z

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Observation 8c8c58b0-839b-40c0-840d-087a0c25bc68 · outbound

This paper cites Prediction with action: Visual policy learning via joint denoising process.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Prediction with action: Visual policy learning via joint denoising process

Reference 13

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Observation dde6585f-c910-4a68-b23a-8afe9f7a6c43 · outbound

This paper cites World Models.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models World Models

Reference 14

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Observation ce1ed570-0573-4068-a645-117cf0b45d06 · outbound

This paper cites NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks

Reference 15

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Observation d2cf1e9c-ae38-4201-9542-e00fb0d69e61 · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models OpenVLA: An Open-Source Vision-Language-Action Model

Reference 16

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Observation 41391cf7-aa3f-4014-9dcf-d350faa40c6a · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:47.995526Z

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Observation 4488247b-6e8c-42bf-a6a1-49782cbee7fe · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 18

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Observation ecbc53fe-a52b-4eb0-8909-1b14e036a0d7 · outbound

This paper cites A path towards autonomous machine intelligence version 0.9.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models A path towards autonomous machine intelligence version 0.9

Reference 19

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Observation c1339ea9-f9f0-49ed-9274-e8db708931bb · outbound

This paper cites Spatial forcing: Implicit spatial representation alignment for vision-language-action model.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Spatial forcing: Implicit spatial representation alignment for vision-language-action model

Reference 20

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Observation 80e99cfe-4d75-4edc-8e32-744c807af7be · outbound

This paper cites Causal World Modeling for Robot Control.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Causal World Modeling for Robot Control

Reference 21

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Observation 98b8ab2c-f921-4fe1-b943-3b43c8d44166 · outbound

This paper cites Genie envisioner: A unified world foundation platform for robotic manipulation.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Genie envisioner: A unified world foundation platform for robotic manipulation

Reference 22

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Observation 26a2dc3f-7a77-4b5d-bfb0-b10b0f2351a3 · outbound

This paper cites Chen, Zhenyu Li, Yang Zhao, Sida Peng, Hengkai Guo, Xiaowei Zhou, Guang Shi, Jiashi Feng, and Bingyi Kang.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Chen, Zhenyu Li, Yang Zhao, Sida Peng, Hengkai Guo, Xiaowei Zhou, Guang Shi, Jiashi Feng, and Bingyi Kang

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:48.020947Z

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Observation 27e78309-e02a-45f0-bea3-19508a1355a4 · outbound

This paper cites Evo-0: Vision-language-action model with implicit spatial understanding.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Evo-0: Vision-language-action model with implicit spatial understanding

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:48.025113Z

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Observation be1497b2-92a0-40b9-85c5-72682119220d · outbound

This paper cites LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:48.029562Z

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Observation 0de3e8b0-1087-4239-8caf-ea5cf5cd2aef · outbound

This paper cites LDA-1B : Scaling latent dynamics action model via universal embodied data ingestion.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models LDA-1B : Scaling latent dynamics action model via universal embodied data ingestion

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:48.033852Z

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Observation 324deabb-cbce-4e2d-ad93-d1774e7a40b0 · outbound

This paper cites Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:48.038045Z

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Observation 4c245f2a-47c9-43d4-84d2-30910db36a7a · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Cosmos World Foundation Model Platform for Physical AI

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T04:29:48.043315Z

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Observation 46abd74f-3980-4e42-b8f4-20b8555cfe06 · outbound

This paper cites mimic-video : Video-action models for generalizable robot control beyond VLA s.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models mimic-video : Video-action models for generalizable robot control beyond VLA s

Reference 29

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Observation de93778c-a4cb-4c4b-b9d2-8f19727bcd0a · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models FAST: Efficient Action Tokenization for Vision-Language-Action Models

Reference 30

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Observation 716a390c-f6e8-46b3-975f-c588f8140822 · outbound

This paper cites World Action Models: A Survey.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models World Action Models: A Survey

Reference 31

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Observation 32c32824-b26b-4ffa-955a-e2cf1795d062 · outbound

This paper cites DINOv3.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models DINOv3

Reference 32

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Observation 1041b97c-be14-4232-a8e7-8e454e373539 · outbound

This paper cites ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver

Reference 33

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Observation 2a7ac604-bd01-4f7c-ad7a-95e2e290ee9f · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 34

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Observation 183b9e5d-dd94-49d1-ac76-0afbcddac176 · outbound

This paper cites RepWAM: World Action Modeling with Representation Visual-Action Tokenizers.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models RepWAM: World Action Modeling with Representation Visual-Action Tokenizers

Reference 35

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Observation 0ba81577-a385-4d83-8e11-1fa2e3e91cb8 · outbound

This paper cites Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation

Reference 36

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Observation 5ec1ab36-5b69-4e54-9563-af133ec4d5a2 · outbound

This paper cites FutureVLA : Joint visuomotor prediction for vision-language-action model.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models FutureVLA : Joint visuomotor prediction for vision-language-action model

Reference 37

Resolution: verified exact; doi, observed 2026-08-10T04:29:48.648570Z

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Observation ed0f1e22-d68a-4cea-b41e-d3da08b7c088 · outbound

This paper cites Open-world hand-object interaction video generation based on structure and contact-aware representation.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Open-world hand-object interaction video generation based on structure and contact-aware representation

Reference 38

Resolution: verified exact; doi, observed 2026-08-10T04:29:48.577201Z

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Observation 1cc128ed-4269-4287-9167-056263ce5d7d · outbound

This paper cites S-VAM : Shortcut video-action model by self-distilling geometric and semantic foresight.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models S-VAM : Shortcut video-action model by self-distilling geometric and semantic foresight

Reference 39

Resolution: verified exact; doi, observed 2026-08-10T04:29:48.513712Z

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Observation c4b5b15e-23f9-4823-8839-77fbb5f559dd · outbound

This paper cites StarVLA-$\alpha$: Reducing Complexity in Vision-Language-Action Systems.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models StarVLA-$\alpha$: Reducing Complexity in Vision-Language-Action Systems

Reference 40

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Observation 121f9558-7f04-4ad5-b05c-72ae241ce07f · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models World Action Models are Zero-shot Policies

Reference 41

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Observation dc978ee6-8bfd-4a90-a742-8d82ae340870 · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Reference 42

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Observation 6c7ddad3-3c45-4236-bce6-01599c6d10cc · outbound

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

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 43

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Observation e0f3f362-803f-4634-9317-0c9e4de7af53 · outbound

This paper cites Do World Action Models Generalize Better than VLAs? A Robustness Study.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models Do World Action Models Generalize Better than VLAs? A Robustness Study

Reference 44

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Observation 2c6d7765-6ae1-441b-9c43-fdaa48b0bb94 · outbound

This paper cites FRAPPE : Infusing world modeling into generalist policies via multiple future representation alignment.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models FRAPPE : Infusing world modeling into generalist policies via multiple future representation alignment

Reference 45

Resolution: verified exact; doi, observed 2026-08-10T04:29:48.396455Z

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Observation 35857a76-840a-43df-9679-a9a0136327d4 · outbound

This paper cites FLARE : Robot learning with implicit world modeling.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models FLARE : Robot learning with implicit world modeling

Reference 46

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Observation 96fb89a0-37c9-4ed8-9ec5-ed94ef617ab0 · outbound

This paper cites FlowVLA : Visual chain of thought-based motion reasoning for vision-language-action models.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models FlowVLA : Visual chain of thought-based motion reasoning for vision-language-action models

Reference 47

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Observation 1f828dd3-a70c-4215-b760-a2f89fa6960c · outbound

This paper cites DualCoT-VLA : Visual-linguistic chain of thought via parallel reasoning for vision-language-action models.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models DualCoT-VLA : Visual-linguistic chain of thought via parallel reasoning for vision-language-action models

Reference 48

Resolution: verified exact; doi, observed 2026-08-10T04:29:48.243625Z

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Observation 337cbdce-6142-4b77-a34a-e47d679b8372 · outbound

This paper cites DINO-WM : World models on pre-trained visual features enable zero-shot planning.

Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models DINO-WM : World models on pre-trained visual features enable zero-shot planning

Reference 49

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