Paper Citation Record · LEDGER

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

As of 7 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 14 inbound Pith citation observations for arXiv:2507.01016.

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

pith.paper-citation-record.v1
2507.01016 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:07:26.130586Z

measured 69 of 69 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T20:59:53.042021Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:19:43.485742Z

Reference resolution

55 of 55 outbound references displayed

verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0bb710e7-e1dd-4a4a-9df3-36d5f420dc2e · outbound

This paper cites GPT-4 Technical Report.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers GPT-4 Technical Report

Reference 1

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Observation d2b560d4-2189-4451-aa56-58d7370ba347 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 2

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Observation 8cb96dad-3e34-4e3b-be2a-3df86d9bd178 · outbound

This paper cites Flamingo: A visual language model for few-shot learning.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Flamingo: A visual language model for few-shot learning

Reference 3

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Observation bab2aed8-d8df-48d5-b6d8-f8f3ca6e8650 · outbound

This paper cites Minivla: A better vla with a smaller footprint.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Minivla: A better vla with a smaller footprint

Reference 4

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Observation 9b752740-a23b-42b6-a8c4-1e9ce8e0b41b · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers RT-1: Robotics Transformer for Real-World Control at Scale

Reference 5

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Observation 6df64edd-df2d-43d0-b50b-7a9991989922 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 6

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Source-reported events for the cited work

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Observation d43c688d-cb8a-4c24-815a-9141f9a3bea3 · outbound

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

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation

Reference 7

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Source-reported events for the cited work

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Observation 3a2658ac-b097-4a57-99f2-2d45dbf88426 · outbound

This paper cites Anyvlm: Unified vision-language model for any robot morphology.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Anyvlm: Unified vision-language model for any robot morphology

Reference 8

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Observation d4f6ece7-02f1-4998-ac13-45b3652590c6 · outbound

This paper cites PaLI-X: On Scaling up a Multilingual Vision and Language Model.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers PaLI-X: On Scaling up a Multilingual Vision and Language Model

Reference 9

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Source-reported events for the cited work

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Observation 3827fc8f-d211-4da5-b32d-9e48b3d2b97c · outbound

This paper cites IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI

Reference 10

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Source-reported events for the cited work

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Observation 7457aed0-8bc8-4c67-8070-4a723c9fbbd1 · outbound

This paper cites Diffusion policy: Visuomotor policy learning via action diffu- sion.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Diffusion policy: Visuomotor policy learning via action diffu- sion

Reference 11

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Observation 49ca3dd1-337e-4860-8823-47335f20c2c8 · outbound

This paper cites Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics

Reference 12

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Observation f6a7de39-98df-4cdc-836c-6243442d69a2 · outbound

This paper cites Palm-e: an embod- ied multimodal language model.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Palm-e: an embod- ied multimodal language model

Reference 13

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Observation 97837d45-4a19-4c9f-a7d8-8072d999b00b · outbound

This paper cites Exploiting llm quantization.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Exploiting llm quantization

Reference 14

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Observation f2dbaa8c-661a-4e26-ba7c-87affb1f7875 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Taming transformers for high-resolution image synthesis

Reference 15

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Observation c5c4ba28-880a-40a5-b658-21c9594fb4d5 · outbound

This paper cites RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot

Reference 16

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Source-reported events for the cited work

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Observation 96be1bc3-b35f-431b-b1a5-c6304326c03f · outbound

This paper cites A new algorithm for data compression.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers A new algorithm for data compression

Reference 17

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Observation 743aa2af-c4ba-4d72-96f2-2b3cd9565335 · outbound

This paper cites Act3d: 3d feature field transformers for multi-task robotic manipulation.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Act3d: 3d feature field transformers for multi-task robotic manipulation

Reference 18

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Observation 85db7f8c-2df1-49c7-836d-3b681e7bcffb · outbound

This paper cites Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning

Reference 19

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Observation b1115345-e57e-4ec5-a187-8b9c1ed1f47e · outbound

This paper cites Deep Reinforcement Learning in Parameterized Action Space.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Deep Reinforcement Learning in Parameterized Action Space

Reference 20

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Observation 8e9902a1-93fd-498e-b383-c9e4935b72b7 · outbound

This paper cites CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Reference 21

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Observation 13dca03f-3454-44ce-8b2e-858468f84538 · outbound

This paper cites Rlbench: The robot learning benchmark & learning environment.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Rlbench: The robot learning benchmark & learning environment

Reference 22

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Observation 398ef956-5728-4acf-aeae-20f2aa4fcf33 · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Pyramidal flow matching for efficient video generative modeling

Reference 23

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Observation 60582574-bb70-4fc5-abd2-93782b851e18 · outbound

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

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers OpenVLA: An Open-Source Vision-Language-Action Model

Reference 24

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Observation aa408865-f62b-4e67-8fa0-68500444dcf2 · outbound

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

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 25

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Observation ab9bdf39-151d-42fc-93a5-b7188949b3f1 · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Behavior Generation with Latent Actions

Reference 26

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Observation 12ce03b6-eb68-4fdd-b832-d35b9d18ff2f · outbound

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

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Reference 27

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Observation ff2f85e6-844b-4225-8780-158474d501a5 · outbound

This paper cites Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation

Reference 28

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Observation c61f6e63-fbab-4d01-a09e-f871f4665d8d · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Language Models are Few-Shot Learners

Reference 29

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Observation 2dc1c629-12aa-4ffc-b9c5-24dd9705b76a · outbound

This paper cites Quest: Self-supervised skill abstractions for learning continuous control.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Quest: Self-supervised skill abstractions for learning continuous control

Reference 30

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Observation 5beecf7a-5133-43f5-a2de-2873d75a10cf · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations

Reference 31

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Observation 2b13a5cb-123d-45f7-a071-a5d63ffe1527 · outbound

This paper cites Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0

Reference 32

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Observation 0c87a25f-e31b-4a1c-bcc9-b8cbf4155947 · outbound

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

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers FAST: Efficient Action Tokenization for Vision-Language-Action Models

Reference 33

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Observation 49f8508b-3bab-41b6-9b32-6d4ba7b90ecb · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Language models are unsuper- vised multitask learners

Reference 34

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Observation 3a536382-8929-4bb4-a7a0-e36e558a26ef · outbound

This paper cites Scalable Image Tokenization with Index Backpropagation Quantization.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Scalable Image Tokenization with Index Backpropagation Quantization

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Observation 7366d8dd-f706-4cfe-b1e1-b8382b733708 · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers LLM Pruning and Distillation in Practice: The Minitron Approach

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Observation 4db8a6af-59f3-4159-a494-9b86e285c1fe · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

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Observation 8554926e-dcd0-4b2a-93ab-00b3c145a3de · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Octo: An Open-Source Generalist Robot Policy

Reference 38

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Observation d9d6a6d4-90fa-462c-9991-fda81792a0fb · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Neural discrete representation learning

Reference 39

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Observation 9c69885d-71c4-4ad6-b823-a8a55f78fdc6 · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Chatgpt for robotics: Design principles and model abilities

Reference 40

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Observation bd82c91d-c9d7-45fc-a6a3-c4788a484fdb · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Any-point Trajectory Modeling for Policy Learning

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation

Reference 42

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Transferring Foundation Models for Generalizable Robotic Manipulation

Reference 43

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Spatiotemporal Predictive Pre-training for Robotic Motor Control

Reference 44

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning

Reference 45

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Latent Action Pretraining from Videos

Reference 46

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Robotic Control via Embodied Chain-of-Thought Reasoning

Reference 47

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Observation a4a5ee28-9536-481e-b8cc-fca2f56b8fbf · outbound

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Soundstream: An end-to- end neural audio codec

Reference 48

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Observation 296c81bb-282e-4713-b691-debf1cd58ac1 · outbound

This paper cites Moviedreamer: Hierarchical generation for coherent long visual sequence.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Moviedreamer: Hierarchical generation for coherent long visual sequence

Reference 49

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VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Diception: A generalist diffusion model for visual perceptual tasks

Reference 50

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Observation 9b04ccf3-2d15-4542-855f-c4cece5049b7 · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:25.850810Z

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Observation ef8e333e-3baf-4787-8619-ad432f15f447 · outbound

This paper cites VLAS: Vision-Language-Action Model With Speech Instructions For Customized Robot Manipulation.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers VLAS: Vision-Language-Action Model With Speech Instructions For Customized Robot Manipulation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:25.936596Z

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Unavailable: canonical work link unavailable.

Observation 50648549-db24-47ed-9cd1-4360a95c363b · outbound

This paper cites 3D-VLA: A 3D Vision-Language-Action Generative World Model.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers 3D-VLA: A 3D Vision-Language-Action Generative World Model

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:25.998032Z

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Unavailable: canonical work link unavailable.

Observation cb1aa5e6-43e7-4995-b644-82f7e86dbef5 · outbound

This paper cites Point cloud matters: Rethinking the impact of different observation spaces on robot learn- ing.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Point cloud matters: Rethinking the impact of different observation spaces on robot learn- ing

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:26.828145Z

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Observation d873b553-398d-4f19-8b8c-2d544b0d7e47 · outbound

This paper cites SPA: 3D Spatial-Awareness Enables Effective Embodied Representation.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers SPA: 3D Spatial-Awareness Enables Effective Embodied Representation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:26.130586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 3a81d664-dbb7-49fc-8697-3ce1f15be229 · inbound

RynnVLA-002: A Unified Vision-Language-Action and World Model cites this paper.

RynnVLA-002: A Unified Vision-Language-Action and World Model VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T20:59:53.042021Z

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Observation 4f2fbe16-6b13-4c90-9544-c2ded5458320 · inbound

Continually Evolving Skill Knowledge in Vision Language Action Model cites this paper.

Continually Evolving Skill Knowledge in Vision Language Action Model VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-17T06:04:09.248500Z

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Observation 5a469e98-446a-4ff9-8737-5725a9922559 · inbound

Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training cites this paper.

Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T13:29:48.923259Z

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Observation d3391853-c917-4460-8253-b556712ed4f2 · inbound

Learning Native Continuation for Action Chunking Flow Policies cites this paper.

Learning Native Continuation for Action Chunking Flow Policies VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-21T12:40:08.704943Z

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 2b267576-52e1-4a81-b10e-890416b67a99 · inbound

PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies cites this paper.

PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-21T13:05:10.051106Z

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 408a266b-fe64-4d6d-a97c-0ced98d15a1f · inbound

PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies cites this paper.

PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T21:37:14.978308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97714748-41f3-43a9-b146-f3ad49458b1d · inbound

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization cites this paper.

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-13T03:57:12.827282Z

Source-reported events for the cited work

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Observation 6a8e3e34-85de-437e-998b-533c131989ae · inbound

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization cites this paper.

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:15:46.671785Z

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 eb409383-3e7e-4ba8-9645-4bef12279702 · inbound

From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model cites this paper.

From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:06:08.666110Z

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

Observation d7a5fd1e-bd22-4e94-bdcd-8398898ae269 · inbound

From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model cites this paper.

From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:54:58.265667Z

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 3df18ac4-53bf-401e-94a0-bec8be992c4c · inbound

NAC: Neural Action Codec for Vision-Language-Action Models cites this paper.

NAC: Neural Action Codec for Vision-Language-Action Models VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:59:37.911642Z

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 29b1bc9b-80ac-436d-a26e-b6ec5eceff9d · inbound

ARP: Enhancing Quantized Skill Abstractions via Visual Alignment and Iterative Refinement for Robotic Manipulation cites this paper.

ARP: Enhancing Quantized Skill Abstractions via Visual Alignment and Iterative Refinement for Robotic Manipulation VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:19:43.487289Z

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 64cce292-40e0-4212-8839-749231c2e2d0 · inbound

EDAR: Learning Environment-Dependent Action Representations for Robotic Manipulation cites this paper.

EDAR: Learning Environment-Dependent Action Representations for Robotic Manipulation VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-14T05:40:47.306935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f734bcda-218e-4a07-8473-f5a4d39067db · inbound

Kepler-Encoder-v0.1: Towards a Multimodal Embedding Model for Robots cites this paper.

Kepler-Encoder-v0.1: Towards a Multimodal Embedding Model for Robots VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T05:01:26.608329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.