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ActQuant

Publication: ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models. Published May 19, 2026.

arxiv.orgPublished May 19, 2026
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Overview

Publication: ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models. Published May 19, 2026.

Publication information

Publication title
ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models
Authors
Arash Akbari, Arman Akbari, Masih Eskandar, Qitao Tan, Yixiao Chen, Jingwu Luo, Bertha Pangaribuan, Liyun Zhang, Jennifer Dy, Geng Yuan, Xue Lin, Gaowen Liu, Stratis Ioannidis, Yanzhi Wang
Published
May 19, 2026
Last publication revision
Aug 3, 2026
Subject areas
cs.CV, cs.AI
Publication source
arxiv.org · abs/2605.24011v3 ↗

Source: arXiv API · observed Oct 11, 2026.

Source links & provenance

https://arxiv.org/abs/2605.24011 ↗

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github.com

the official implementation of the paper “Re(visiting) Time Series Foundation Models in Finance”.

GitHub stars
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Language
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Code license
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foundation-modeltime-seriesresearch-lab
96 Authority 96 / 100 Cited by 2 resources in this directory 2 discovery sources Directory record updated: 2026-10-11 How scoring works →

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