TempoBridge: Language-Guided Tempo Control for Vision-Language-Action Policies
cs.RO
Submitted: 2026-10-07
Updated: 2026-10-07
Project page: https://lysees.github.io/tempobridge-page
Terminology
Sources
- TempoVLA: Learning Speed-Controllable Vision-Language-Action Policies
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models
- PaliGemma: A versatile 3B VLM for transfer
Related papers
- FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
- MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
- RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving