Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-27T21:57:19.195413Z
Paper Citation Record · LEDGER
As of 5 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2606.07107.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-27T21:57:19.195413Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
41 of 41 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a9bb6995-54bd-44cb-9ff1-96059cd9f1ad · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models RT-1: Robotics Transformer for Real-World Control at Scale
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Octo: An Open-Source Generalist Robot Policy
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge
Reference 13
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models GraphCoT-VLA: A 3D Spatial-Aware Reasoning Vision-Language-Action Model for Robotic Manipulation with Ambiguous Instructions
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Observation f4fa4270-f393-406b-97a6-4c89cde07725 · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models FAST: Efficient Action Tokenization for Vision-Language-Action Models
Reference 17
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
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Observation 7f25fbfc-b49d-4ba4-883e-d50f60f590e1 · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
Reference 19
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
Reference 20
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models MolmoAct: Action Reasoning Models that can Reason in Space
Reference 21
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Observation 04e7d929-150b-4cb2-a099-c465f3a27b73 · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models MolmoAct2: Action Reasoning Models for Real-world Deployment
Reference 22
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Reference 23
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Faster: Toward efficient autoregressive vision language action modeling via neural action tokenization.ArXiv, abs/2512.04952
Reference 24
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Actioncodec: What makes for good action tokenizers.arXiv preprint arXiv:2602.15397
Reference 25
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Unresolved cited work
Reference 26
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Observation 37fba301-a5d6-47aa-a04d-16a4e0c5ced1 · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Unresolved cited work
Reference 27
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Observation 040e54ee-2b64-4b1b-9e13-d34a780fe6d5 · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Evaluating Real-World Robot Manipulation Policies in Simulation
Reference 28
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Reference 29
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
Reference 30
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models WorldVLA: Towards Autoregressive Action World Model
Reference 31
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Quantum error thresholds for gauge-redundant digitiza- tions of lattice field theories
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Reference 37
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Self-Consistency Improves Chain of Thought Reasoning in Language Models
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Observation 7a9eac4a-74fb-4c34-8054-3bb219dba706 · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
Reference 39
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models BridgeData V2: A Dataset for Robot Learning at Scale
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Observation bb9e507e-cf42-4f5c-b0f5-634804e9c5ab · outbound
Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Reference 41
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Coarse-to-Control: Action-Token Planning for Vision-Language-Action Models DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Reference 42
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Reference 43
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No inbound Pith citation observations are available.