The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks
cs.RO, cs.AI, cs.CV
Submitted: 2026-06-26
Updated: 2026-10-11
Terminology
Sources
- OpenVLA: An Open-Source Vision-Language-Action Model
- SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- RT-1: Robotics Transformer for Real-World Control at Scale
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
- RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
- Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
- Causal World Modeling for Robot Control
- World Action Models are Zero-shot Policies
- GigaWorld-Policy: An Efficient Action-Centered World--Action Model
- PaliGemma: A versatile 3B VLM for transfer
- Cosmos World Foundation Model Platform for Physical AI
- Mastering Diverse Domains through World Models
- QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models
- VLA-Cache: Efficient Vision-Language-Action Manipulation via Adaptive Token Caching
- SP-VLA: A Joint Model Scheduling and Token Pruning Approach for VLA Model Acceleration
- SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
- DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
- One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation
- VLASH: Real-Time VLAs via Future-State-Aware Asynchronous Inference
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