D squared-VLA: Dual-Memory Dual-Frequency Vision-Language-Action Model For Long Dynamic Manipulation

arXiv:2609.34792 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-30

Terminology

• Benchmark — 28× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Accuracy — 6× in this paper · explained in 1 episode
• KV cache — 6× in this paper · explained in 3 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Manipulation Score — 4× in this paper
• Ablation Studies — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Action Chunking — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 7 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• VLA Models — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes

Sources

• PaliGemma: A versatile 3B VLM for transfer
• Real-Time Execution of Action Chunking Flow Policies
• RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
• InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
• Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
• StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
• RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies
• SeedPolicy: Horizon Scaling via Self-Evolving Diffusion Policy for Robot Manipulation
• Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
• ReMem-VLA: Empowering Vision-Language-Action Model with Memory via Dual-Level Recurrent Queries
• CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation
• Vision-Language Foundation Models as Effective Robot Imitators
• FAVLA: A Force-Adaptive Fast-Slow VLA model for Contact-Rich Robotic Manipulation
• RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• FAST: Efficient Action Tokenization for Vision-Language-Action Models
• SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
• MemER: Scaling Up Memory for Robot Control via Experience Retrieval
• TempoFit: Plug-and-Play Layer-Wise Temporal KV Memory for Long-Horizon Vision-Language-Action Manipulation
• VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model

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