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Official implementation of ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models
The main features of arashakb/actquant are: Embodied Foundation Models.
Projects with overlapping indexed features include: alibaba-damo-academy/worldvla — RynnVLA-002: A Unified Vision-Language-Action and World Model. amap-cvlab/abot-manipulation — ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning. beingbeyond/being-h — Being-H is BeingBeyond's family of human-centric embodied foundation models. beingbeyond/being-h0 — Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos (ICML 2026). buoyancy99/large-video-planner — This repo provides training and inference code for the paper "Large Video Planner Enables Generalizable Robot Control". agibottech/genie-envisioner — Join our WeChat Group.
RynnVLA-002: A Unified Vision-Language-Action and World Model
ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
Being-H is BeingBeyond's family of human-centric embodied foundation models.
