BridgeWAM: Bridging Video and Action Experts via Latent Bridge Queries
cs.RO, cs.CV
Submitted: 2026-10-10
Updated: 2026-10-10
Code: https://github.com/jxfang04/BridgeWAM-code
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Motus: A Unified Latent Action World Model
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- RT-1: Robotics Transformer for Real-World Control at Scale
- AHA-WAM:Asynchronous Horizon-Adaptive World-Action Modeling with Observation-Guided Context Routing
- WorldVLA: Towards Autoregressive Action World Model
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
- DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos
- OpenVLA: An Open-Source Vision-Language-Action Model
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
- DTP: A Simple yet Effective Distracting Token Pruning Framework for Vision-Language Action Models
- Causal World Modeling for Robot Control
- LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
- Transfer between Modalities with MetaQueries
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- Artificial Foveated Perception for Mitigating Shortcut Learning in Robotic Foundation Models
- Wan: Open and Advanced Large-Scale Video Generative Models
- Video Generation Models are General-Purpose Vision Learners
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