Behavior-Aligned Action Tokenization for Robot Policy Learning
cs.RO
Submitted: 2026-09-23
Updated: 2026-09-23
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models
- OpenVLA: An Open-Source Vision-Language-Action Model
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- FAST: Efficient Action Tokenization for Vision-Language-Action Models
- OAT: Ordered Action Tokenization
- ActionCodec: What Makes for Good Action Tokenizers
- X-Tokenizer: A Multimodal Action Tokenizer for Vision-Language-Action Pretraining
- Finite Scalar Quantization: VQ-VAE Made Simple
- RT-1: Robotics Transformer for Real-World Control at Scale
- Time-Contrastive Networks: Self-Supervised Learning from Video
- Hierarchical Latent Action Model
- Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
- Octo: An Open-Source Generalist Robot Policy
- Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
- LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better
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