Paper Citation Record · LEDGER

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 9 inbound Pith citation observations for arXiv:2509.09090.

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

pith.paper-citation-record.v1
2509.09090 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:47:08.931435Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:08:13.317526Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:45:42.923029Z

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy0
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d935dbba-20ba-4735-800f-079d712a1010 · outbound

This paper cites CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.797170Z

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Observation 5f3307b6-c5a2-47da-816b-9ff403a6365d · outbound

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

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.802413Z

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Observation c6ec425a-3e67-4566-a944-b43796e8289c · outbound

This paper cites A White Paper on Neural Network Quantization.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models A White Paper on Neural Network Quantization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.812712Z

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Observation 608c33f8-2cf2-4590-9d16-c1836852afc9 · outbound

This paper cites URL http://dx.doi.org/10.1109/HPCA51647.2021.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models URL http://dx.doi.org/10.1109/HPCA51647.2021

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.818085Z

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Observation c3432691-8733-4ffd-aab5-4797d67bc395 · outbound

This paper cites Atom: Low-bit Quantization for Efficient and Accurate LLM Serving.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Atom: Low-bit Quantization for Efficient and Accurate LLM Serving

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.829325Z

Source-reported events for the cited work

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Observation 4d0ff860-603d-4512-a3da-9917d0cdf2db · outbound

This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.834651Z

Source-reported events for the cited work

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Observation aaae707c-ceb2-4163-ad59-77df1e7386f3 · outbound

This paper cites Pruning vs Quantization: Which is Better?.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Pruning vs Quantization: Which is Better?

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.839632Z

Source-reported events for the cited work

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Observation 24c9c73c-6729-45a1-b3a5-b266ece0f77e · outbound

This paper cites Pruning and Quantization for Deep Neural Network Acceleration: A Survey.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Pruning and Quantization for Deep Neural Network Acceleration: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.845268Z

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Observation e319e8a0-699c-4f74-8020-af47f026ec57 · outbound

This paper cites doi:10.3389/frai.2021.676564.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models doi:10.3389/frai.2021.676564

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.850397Z

Source-reported events for the cited work

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Observation ab771970-2e0f-4ef3-9662-e90719abfbf4 · outbound

This paper cites Fit and Prune: Fast and Training-free Visual Token Pruning for Multi-modal Large Language Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Fit and Prune: Fast and Training-free Visual Token Pruning for Multi-modal Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.863100Z

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Observation fff96ee7-9324-463c-a844-b2e7dfdc9fd9 · outbound

This paper cites A Survey on Model Compression for Large Language Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models A Survey on Model Compression for Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.878839Z

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Observation ab9bc3ca-ba4e-46e5-be78-8ce8e345a10c · outbound

This paper cites Quantization-Aware Imitation-Learning for Resource-Efficient Robotic Control.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Quantization-Aware Imitation-Learning for Resource-Efficient Robotic Control

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.888490Z

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Observation a5d1814c-87d5-4969-8a94-3856598e2871 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.893647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0145e2e5-705f-43f1-907e-7b98148969d5 · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.898636Z

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Unavailable: canonical work link unavailable.

Observation 1319fedc-277e-4ec4-ba9b-b618e122e71e · outbound

This paper cites FlatQuant: Flatness Matters for LLM Quantization.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models FlatQuant: Flatness Matters for LLM Quantization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.903863Z

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Observation b6e18987-f9be-456d-8b71-e8b2d7397529 · outbound

This paper cites An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.908760Z

Source-reported events for the cited work

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Observation 308d8149-08bb-4df9-a095-1195cee4d6ec · outbound

This paper cites Token Merging: Your ViT But Faster.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Token Merging: Your ViT But Faster

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.913310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b59d997-6657-4795-9fa9-181e2d445d87 · outbound

This paper cites EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.917977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91e80d00-de51-48f1-98dc-69ff54bba66b · outbound

This paper cites Rongyu Zhang, Menghang Dong, Yuan Zhang, Liang Heng, Xiaowei Chi, Gaole Dai, Li Du, Yuan Du, and Shanghang Zhang.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Rongyu Zhang, Menghang Dong, Yuan Zhang, Liang Heng, Xiaowei Chi, Gaole Dai, Li Du, Yuan Du, and Shanghang Zhang

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.922619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a469e6e8-31ea-4500-94a1-439f5ccebc91 · outbound

This paper cites Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.926803Z

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Unavailable: canonical work link unavailable.

Observation d7007b9a-bfef-44c9-8485-9b40816a0dad · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.931435Z

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Unavailable: canonical work link unavailable.

Observation e1de2411-b5ec-4270-9549-90aa91300aa4 · outbound

This paper cites PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.874157Z

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Observation b726098f-75a2-4725-911e-85948c2b5c9e · outbound

This paper cites Single Shot 6D Object Pose Estimation.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Single Shot 6D Object Pose Estimation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.868990Z

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Observation 8e164972-68af-458e-a1a3-67e8b39dc80c · outbound

This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.807509Z

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Observation 74e66191-80ba-4e3d-90c3-8155285b68f7 · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models PaLM-E: An Embodied Multimodal Language Model

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.883747Z

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Observation fe389765-247a-485d-a60f-eea2285a053d · outbound

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

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models OpenVLA: An Open-Source Vision-Language-Action Model

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.791525Z

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Observation 43d2f4d2-16b6-4743-8477-11624786dccc · outbound

This paper cites QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.823245Z

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Pith citing papers

Observation 7a2ca6d5-ad77-4bd1-9a60-deb5ed461716 · inbound

Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey cites this paper.

Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T09:08:13.317526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a68dd65-7199-439d-97d3-e7258ed9e850 · inbound

OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism cites this paper.

OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-21T11:50:03.821915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 24ae6786-cd7c-435f-86b1-9b53efba5d75 · inbound

FASTER: Rethinking Real-Time Flow VLAs cites this paper.

FASTER: Rethinking Real-Time Flow VLAs SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:05:15.417908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 10cd56d4-3b81-4679-93d6-3d5b59c40347 · inbound

FASTER: Rethinking Real-Time Flow VLAs cites this paper.

FASTER: Rethinking Real-Time Flow VLAs SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-21T10:50:00.910305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation adf17fdd-6a09-4179-aabc-b971325d0861 · inbound

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model cites this paper.

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:50:51.318338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 53065b05-12a8-4036-8d3c-1ea7355672c0 · inbound

DA-PTQ: Drift-Aware Post-Training Quantization for Efficient Vision-Language-Action Models cites this paper.

DA-PTQ: Drift-Aware Post-Training Quantization for Efficient Vision-Language-Action Models SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:06:05.219311Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 86528096-0256-4486-aaf9-eb94c8a19256 · inbound

Towards Joint Quantization and Token Pruning of Vision-Language Models cites this paper.

Towards Joint Quantization and Token Pruning of Vision-Language Models SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:01:49.019417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b30eee6c-ec9e-47cb-8a6c-b6f96814cf84 · inbound

Latent Bridge: Feature Delta Prediction for Efficient Dual-System Vision-Language-Action Model Inference cites this paper.

Latent Bridge: Feature Delta Prediction for Efficient Dual-System Vision-Language-Action Model Inference SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:11:14.246348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 54cbdec2-78f7-4413-9e67-07efddbe9c45 · inbound

Revisiting Parameter Redundancy in Vision-Language-Action Models: Insights from VLM-to-VLA Adaptation cites this paper.

Revisiting Parameter Redundancy in Vision-Language-Action Models: Insights from VLM-to-VLA Adaptation SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:45:42.924464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.