Paper Citation Record · LEDGER

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

As of 7 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2607.13960.

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

pith.paper-citation-record.v1
2607.13960 v3

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:16:53.139337Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:59:27.939168Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T14:52:36.051441Z

Reference resolution

68 of 68 outbound references displayed

verified exact0
verified fuzzy0
unresolved68
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81faaba5-0763-4ce7-bbe1-9128ae36e20e · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Cosmos World Foundation Model Platform for Physical AI

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:51.468627Z

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Unavailable: canonical work link unavailable.

Observation 1d25b611-2925-4a85-b2b2-b76883d1024e · outbound

This paper cites Cosmos 3: Omnimodal World Models for Physical AI.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Cosmos 3: Omnimodal World Models for Physical AI

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:51.556914Z

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Observation babce225-27ae-4451-b350-a6b723bbe9cf · outbound

This paper cites Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:51.693644Z

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Observation d8e77484-50ff-43b8-9933-97ce411d7847 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Motus: A unified latent action world model

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:51.899948Z

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Observation 5a4b76ed-6203-4d2c-8562-57f4e686a7a2 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.108500Z

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Observation 60c9e266-4eb8-445b-ae5d-ea01856f42d6 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.225686Z

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Observation 77976c29-3576-485f-8742-f29c62330568 · outbound

This paper cites AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.333915Z

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Observation 8f28fe47-9861-4ba3-b6f8-e716e3451c1b · outbound

This paper cites WorldVLA: Towards Autoregressive Action World Model.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch WorldVLA: Towards Autoregressive Action World Model

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.499150Z

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Observation 80e94dfd-9b4c-4b44-8e76-1396f1a68e56 · outbound

This paper cites Lawam: Latent world action models for efficient dynamics-aware robot policies.arXiv preprint arXiv:2606.15768, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Lawam: Latent world action models for efficient dynamics-aware robot policies.arXiv preprint arXiv:2606.15768, 2026

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.575487Z

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Observation 5cdc9b33-c63c-4668-bd50-fa32edd63f59 · outbound

This paper cites Unimax: Fairer and more effective language sampling for large-scale multilingual pretraining.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Unimax: Fairer and more effective language sampling for large-scale multilingual pretraining

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.653824Z

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Observation c07ed61b-df65-4235-b0ff-9d5e146efd88 · outbound

This paper cites Emma: Generalizing real-world robot manipulation via generative visual transfer.arXiv preprint arXiv:2509.22407, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Emma: Generalizing real-world robot manipulation via generative visual transfer.arXiv preprint arXiv:2509.22407, 2025

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.735830Z

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Observation fa5e265c-d13c-4a96-b1bf-b72221d64e80 · outbound

This paper cites Learning universal policies via text-guided video generation.Advances in neural information processing systems, 36:9156–9172, 2023.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Learning universal policies via text-guided video generation.Advances in neural information processing systems, 36:9156–9172, 2023

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.800361Z

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Observation 82a573c0-c1bb-4763-9889-8c269e849b00 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Scaling rectified flow transformers for high-resolution image synthesis

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.871383Z

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Observation f5994737-809d-4e45-ad7e-2d7e255c052e · outbound

This paper cites $\pi^{*}_{0.6}$: a VLA That Learns From Experience.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch $\pi^{*}_{0.6}$: a VLA That Learns From Experience

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.931575Z

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Observation 2468ae23-d88c-4741-9bbd-173d0461a61f · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.979043Z

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Observation ba7bc83f-654d-4bc5-9c77-c9215aa66c3f · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.982239Z

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Observation ab16b418-1055-4637-92fe-4f92feb62da8 · outbound

This paper cites WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.985410Z

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Observation 22e95b37-6ee4-43eb-a173-e1b20b5f41f5 · outbound

This paper cites autoresearch, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch autoresearch, 2026

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.988893Z

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Observation 5e11643f-9ba0-43a2-b39f-4f0f9ee238ff · outbound

This paper cites Freeaction: Training-free techniques for enhanced fidelity of trajectory-to-video generation.arXiv preprint arXiv:2509.24241, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Freeaction: Training-free techniques for enhanced fidelity of trajectory-to-video generation.arXiv preprint arXiv:2509.24241, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.991539Z

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Observation 045f3ec5-38d5-4e8d-a152-7c4839b664f7 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch A path towards autonomous machine intelligence version 0.9

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.994236Z

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Observation 4e7d7400-9f16-4fb5-a35b-1f1e02d55093 · outbound

This paper cites Mimicdreamer: Aligning human and robot demonstrations for scalable vla training.arXiv preprint arXiv:2509.22199, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Mimicdreamer: Aligning human and robot demonstrations for scalable vla training.arXiv preprint arXiv:2509.22199, 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:52.997448Z

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Observation f7463fcd-5db7-4323-b88e-2d205fdac65e · outbound

This paper cites Causal World Modeling for Robot Control.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Causal World Modeling for Robot Control

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.000407Z

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Observation 6515e2db-737a-42b4-901d-1e096fb72f73 · outbound

This paper cites Flow Matching for Generative Modeling.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Flow Matching for Generative Modeling

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.003738Z

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Observation ac94fcc8-2632-403f-8649-9758b09b65dd · outbound

This paper cites Timestep embedding tells: It’s time to cache for video diffusion model.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Timestep embedding tells: It’s time to cache for video diffusion model

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.007000Z

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Observation 222a2b9b-792b-42a4-8523-e7d1b5fdc4b2 · outbound

This paper cites Robotransfer: Controllable geometry-consistent video diffusion for manipulation policy transfer.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Robotransfer: Controllable geometry-consistent video diffusion for manipulation policy transfer

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.009824Z

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Observation c7cf7d4b-ef9f-416b-8dd3-c10caa3b1530 · outbound

This paper cites Rdt-1b: a diffusion foundation model for bimanual manipulation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Rdt-1b: a diffusion foundation model for bimanual manipulation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.013067Z

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Observation e65b3ed6-65b7-459c-be83-84e080132ed3 · outbound

This paper cites Being-H0.7: A Latent World-Action Model from Egocentric Videos.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Being-H0.7: A Latent World-Action Model from Egocentric Videos

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.016000Z

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Observation 159fbbe0-8ae9-4750-8623-802e11e201f7 · outbound

This paper cites ViVa: A Video-Generative Value Model for Robot Reinforcement Learning.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch ViVa: A Video-Generative Value Model for Robot Reinforcement Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.019586Z

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Observation 84001fe0-c77a-4c4b-9298-2e1b46168bff · outbound

This paper cites Dit4dit: Jointly modeling video dynamics and actions for generalizable robot control.arXiv preprint arXiv:2603.10448,.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Dit4dit: Jointly modeling video dynamics and actions for generalizable robot control.arXiv preprint arXiv:2603.10448,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.022701Z

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Observation 59813907-6f9a-448b-bee4-86275d0e5643 · outbound

This paper cites ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.025755Z

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Observation 7f33f67e-8385-4438-a9f9-1609f7d39d74 · outbound

This paper cites Swiftvla: Unlocking spatiotemporal dynamics for lightweight vla models at minimal overhead.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Swiftvla: Unlocking spatiotemporal dynamics for lightweight vla models at minimal overhead

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.029636Z

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Observation 41af6501-2b9c-4a8f-8cfe-8d0f919a750f · outbound

This paper cites mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.032905Z

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Observation 30ece4c3-f35d-461f-afc8-a7b7f14a1335 · outbound

This paper cites Videovla: Video generators can be generalizable robot manipulators.Advances in neural information processing systems, 38:95597–95621, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Videovla: Video generators can be generalizable robot manipulators.Advances in neural information processing systems, 38:95597–95621, 2026

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.036196Z

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Observation ea5750a5-3377-49a2-824d-8ff8f7b4e8ad · outbound

This paper cites World guidance: World modeling in condition space for action generation.arXiv preprint arXiv:2602.22010, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch World guidance: World modeling in condition space for action generation.arXiv preprint arXiv:2602.22010, 2026

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.039159Z

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Observation c3adf8a5-f273-422d-af66-69b6facc424a · outbound

This paper cites AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.041846Z

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Observation 81fcf3f0-f34e-41e1-a23a-8b16f32775ea · outbound

This paper cites Gigabrain-0: A world model-powered vision-language-action model.arXiv preprint arXiv:2510.19430, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Gigabrain-0: A world model-powered vision-language-action model.arXiv preprint arXiv:2510.19430, 2025

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.045406Z

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Observation 7cbb8625-d910-46b4-8299-afe91d875d3d · outbound

This paper cites Gigabrain-0.5 m*: a vla that learns from world model-based reinforcement learning.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Gigabrain-0.5 m*: a vla that learns from world model-based reinforcement learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.048225Z

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Observation db5c560a-1848-43f8-bfd4-a6672ac7135f · outbound

This paper cites Gigaworld-0: World models as data engine to empower embodied ai.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Gigaworld-0: World models as data engine to empower embodied ai

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.051352Z

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Observation 828fb644-3e25-4b96-acba-6bdf3bb4c945 · outbound

This paper cites GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.054370Z

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Observation ca3b4035-31c5-4568-997f-bb7713de020d · outbound

This paper cites Motubrain: An Advanced World Action Model for Robot Control.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Motubrain: An Advanced World Action Model for Robot Control

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.057505Z

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Observation 99d73420-2d6b-4919-8202-08f2e4b6ac0f · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Wan: Open and Advanced Large-Scale Video Generative Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.060585Z

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Observation 5b1d2416-3b42-4457-8444-9e3082bb482e · outbound

This paper cites EmbodieDreamer: Advancing Real2Sim2Real Transfer for Policy Training via Embodied World Modeling.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch EmbodieDreamer: Advancing Real2Sim2Real Transfer for Policy Training via Embodied World Modeling

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.063727Z

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Observation bc282f01-ba83-4c0a-8d79-19f53ef1c47c · outbound

This paper cites Humandreamer-x: Photorealistic single-image human avatars reconstruction via gaussian restoration.arXiv preprint arXiv:2504.03536, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Humandreamer-x: Photorealistic single-image human avatars reconstruction via gaussian restoration.arXiv preprint arXiv:2504.03536, 2025

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.066630Z

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Observation 65930336-6fa1-4fb0-845b-e68251452a6a · outbound

This paper cites ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.069617Z

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Observation 38d97754-3db9-429b-80f5-58f896e35cbb · outbound

This paper cites Drivedreamer: Towards real-world-drive world models for autonomous driving.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Drivedreamer: Towards real-world-drive world models for autonomous driving

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.072452Z

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Observation 0f539b69-ceb2-4482-bd59-174de125e61f · outbound

This paper cites WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.075596Z

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Observation 2dfd3ecc-55a7-4184-9968-c72f9945879b · outbound

This paper cites Egovid-5m: A large-scale video-action dataset for egocentric videos generation.Advances in Neural Information Processing Systems, 38, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Egovid-5m: A large-scale video-action dataset for egocentric videos generation.Advances in Neural Information Processing Systems, 38, 2026

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.078807Z

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Observation c951ba54-fe9f-4c5e-b278-e6954a80343d · outbound

This paper cites Unleashing large-scale video generative pre-training for visual robot manipulation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Unleashing large-scale video generative pre-training for visual robot manipulation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.081537Z

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Observation 07de1111-fb3f-4882-8fe0-9c06efbab001 · outbound

This paper cites RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.084538Z

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Observation acc6125a-cb03-47c6-8bec-9d1dbbd6b11e · outbound

This paper cites A Pragmatic VLA Foundation Model.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch A Pragmatic VLA Foundation Model

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.087819Z

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Observation 62a1fd9c-bbcc-4b8a-a679-944154b2e172 · outbound

This paper cites Pandora: Towards General World Model with Natural Language Actions and Video States.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Pandora: Towards General World Model with Natural Language Actions and Video States

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.090709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c82ef15-1974-4bfc-b7f2-e010d10b3570 · outbound

This paper cites S-vam: Shortcut video-action model by self-distilling geometric and semantic foresight.arXiv preprint arXiv:2603.16195, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch S-vam: Shortcut video-action model by self-distilling geometric and semantic foresight.arXiv preprint arXiv:2603.16195, 2026

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.093687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f8d4b39-a49b-4f45-84c4-3dd93d6a9a55 · outbound

This paper cites Vla-r1: Enhancing reasoning in vision-language-action models.arXiv preprint arXiv:2510.01623, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Vla-r1: Enhancing reasoning in vision-language-action models.arXiv preprint arXiv:2510.01623, 2025

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.096363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e2be43d-316a-4b64-bad9-c41302c51ee2 · outbound

This paper cites HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.099063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b487279f-f53f-4c5c-b432-2b1d050e526d · outbound

This paper cites Gigaworld-policy: An efficient action-centered world–action model.arXiv preprint arXiv:2603.17240, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Gigaworld-policy: An efficient action-centered world–action model.arXiv preprint arXiv:2603.17240, 2026

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.101931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 777d1df7-f0ff-4dba-b766-65dada147621 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch World Action Models are Zero-shot Policies

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.104585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e586a8d-d2b7-4bc0-a9a8-ac2f7f8195a1 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.107666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b72f99b-1fd9-434e-aefa-3bba96e397d8 · outbound

This paper cites Igniting vlms toward the embodied space.arXiv preprint arXiv:2509.11766, 2025.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Igniting vlms toward the embodied space.arXiv preprint arXiv:2509.11766, 2025

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.110746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9bd6962-2532-4ba5-b804-06f33509fbf1 · outbound

This paper cites Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.113554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17dce28c-202d-4eb2-9602-11fbc2fd2ff2 · outbound

This paper cites Drivedreamer4d: World models are effective data machines for 4d driving scene representation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Drivedreamer4d: World models are effective data machines for 4d driving scene representation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.116430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 600fa4ed-481e-44d1-830a-5dda5b12f0a1 · outbound

This paper cites Recondreamer++: Harmonizing generative and reconstructive models for driving scene representation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Recondreamer++: Harmonizing generative and reconstructive models for driving scene representation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.119201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c8cc1bc-e571-4309-b386-c466cf81b9d0 · outbound

This paper cites Drivedreamer-2: Llm-enhanced world models for diverse driving video generation.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Drivedreamer-2: Llm-enhanced world models for diverse driving video generation

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.121822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ba7ecb-287c-494c-96b9-57ef67030699 · outbound

This paper cites Unidrivedreamer: A single-stage multimodal world model for autonomous driving.arXiv preprint arXiv:2602.02002, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Unidrivedreamer: A single-stage multimodal world model for autonomous driving.arXiv preprint arXiv:2602.02002, 2026

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.124492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0067d6ff-ed34-47cd-974c-ce5b0cfb1df7 · outbound

This paper cites Robodreamer: learning compositional world models for robot imagination.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Robodreamer: learning compositional world models for robot imagination

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.127533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc1fda4b-8a03-457a-adac-fc12d0523c6c · outbound

This paper cites Drivedreamer-policy: A geometry-grounded world-action model for unified generation and planning.arXiv preprint arXiv:2604.01765, 2026.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Drivedreamer-policy: A geometry-grounded world-action model for unified generation and planning.arXiv preprint arXiv:2604.01765, 2026

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.130193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 327c4baf-ae85-4e77-b149-0a71b3414ab9 · outbound

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

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.133370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2818f538-239b-43af-9ef7-d7f8fb425105 · outbound

This paper cites Aether: Geometric-aware unified world modeling.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Aether: Geometric-aware unified world modeling

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.136626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 222db407-7b16-42ae-b6bc-f76c00cbccde · outbound

This paper cites Is sora a world simulator? a comprehensive survey on general world models and beyond.arXiv preprint arXiv:2405.03520, 2024.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch Is sora a world simulator? a comprehensive survey on general world models and beyond.arXiv preprint arXiv:2405.03520, 2024

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-02T03:16:53.139337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation da858a85-9002-4215-b1cb-ba70cb99ce5c · inbound

PhyAI: Real-Time Physical AI at the Edge, Scalable Rollouts in the Cloud cites this paper.

PhyAI: Real-Time Physical AI at the Edge, Scalable Rollouts in the Cloud GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T14:52:36.054142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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

DreamWAM: Beyond RGB Future Prediction for World Action Models cites this paper.

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

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T11:59:27.939168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.