Paper Citation Record · LEDGER

Learning 4D Geometric Priors for Inference-Efficient World Action Models

As of 22 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 1 inbound Pith citation observation for arXiv:2607.05468.

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

pith.paper-citation-record.v1
2607.05468 v1

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T14:23:57.266710Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:49:36.861441Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

79 of 79 outbound references displayed

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External citation measurements

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Outbound references

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 2

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models 2025 , editor=

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Conference on Robot Learning , year=

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Learning 4D Geometric Priors for Inference-Efficient World Action Models International Conference on Learning Representations , year=

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Learning 4D Geometric Priors for Inference-Efficient World Action Models IEEE/CVF International Conference on Computer Vision , pages=

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Learning 4D Geometric Priors for Inference-Efficient World Action Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Any3D-VLA: Enhancing VLA Robustness via Diverse Point Clouds

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

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Learning 4D Geometric Priors for Inference-Efficient World Action Models $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

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Learning 4D Geometric Priors for Inference-Efficient World Action Models J.; Pertsch, K.; Karamcheti, S.; Xiao, T.; Balakrishna, A.; Nair, S.; Rafailov, R.; Foster, E

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Causal World Modeling for Robot Control

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Learning 4D Geometric Priors for Inference-Efficient World Action Models WAM4D: Fast 4D World Action Model via Spatial Register Tokens

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs

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Learning 4D Geometric Priors for Inference-Efficient World Action Models FAST: Efficient Action Tokenization for Vision-Language-Action Models

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 68

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

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Learning 4D Geometric Priors for Inference-Efficient World Action Models DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation

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Learning 4D Geometric Priors for Inference-Efficient World Action Models GeoVLA: Empowering 3D Representations in Vision-Language-Action Models

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Motubrain: An Advanced World Action Model for Robot Control

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Wan: Open and Advanced Large-Scale Video Generative Models

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 74

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Learning 4D Geometric Priors for Inference-Efficient World Action Models World Action Models: The Next Frontier in Embodied AI

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unified Vision-Language-Action Model

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Next Forcing: Causal World Modeling with Multi-Chunk Prediction

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 78

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 79

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Learning 4D Geometric Priors for Inference-Efficient World Action Models World Action Models are Zero-shot Policies

Reference 80

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Fast-WAM: Do World Action Models Need Test-time Future Imagination?

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 82

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Learning 4D Geometric Priors for Inference-Efficient World Action Models Unresolved cited work

Reference 83

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Learning 4D Geometric Priors for Inference-Efficient World Action Models X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

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Pith citing papers

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ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts cites this paper.

ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts Learning 4D Geometric Priors for Inference-Efficient World Action Models

Reference 45

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