DR-VLA: Learning Human-Like Quadruped Navigation from Egocentric Web Videos via Domain-Invariant Scene Representations
cs.RO
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: 16 pages, 3 figures, 6 tables
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- Emerging Properties in Unified Multimodal Pretraining
- Co-training with Ego-centric Video and Demonstration for Robot Navigation Task
- Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
- Being-H0.7: A Latent World-Action Model from Egocentric Videos
- F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions
- Cosmos World Foundation Model Platform for Physical AI
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision
- DINOv3
- SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving
- GrandTour: A Legged Robotics Dataset in the Wild for Multi-Modal Perception and State Estimation
- From Foundation to Application: Improving VLA Models in Practice
- World Action Models are Zero-shot Policies
- DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving
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