ChunkAct: Action Chunking for Agentic Robotics

arXiv:2610.18874 · cs.RO, cs.AI, cs.CL, cs.CV · Submitted 2026-10-13 · Read on arXiv

cs.RO, cs.AI, cs.CL, cs.CV

Submitted: 2026-10-13

Updated: 2026-10-13

Code: https://github.com/openai/codex

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Action Chunking — 1× in this paper · explained in 2 episodes

Sources

• RT-H: Action Hierarchies Using Language
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• RT-1: Robotics Transformer for Real-World Control at Scale
• UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
• WorldVLA: Towards Autoregressive Action World Model
• LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
• CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
• Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
• VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
• Inner Monologue: Embodied Reasoning through Planning with Language Models
• NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks
• Agent as Policy for Robotic Manipulation
• Memory Transfer Planning: LLM-driven Context-Aware Code Adaptation for Robot Manipulation
• AI Agents That Matter
• Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
• Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
• OpenVLA: An Open-Source Vision-Language-Action Model
• Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation
• RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis
• MemGPT: Towards LLMs as Operating Systems

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• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies