15 papers
RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance
Dongchi Huang, Hongyin Zhang, Bohan Hou +12
General-purpose reward models are increasingly the bottleneck for scaling robot learning, yet the recipe for learning value-related capabilities from large-scale heterogeneous corp…
World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems
Runze Li, Hongyin Zhang, Junxi Jin +5
Vision-Language-Action (VLA) models have emerged as a promising paradigm for building embodied agents that ground perception and language into action. However, most existing approa…
MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation
Yang Liu, Pengxiang Ding, Tengyue Jiang +10
Vision-Language-Action (VLA) models map visual observations and natural-language instructions to robot actions; however, hierarchical and autoregressive paradigms often incur archi…
Information-Theoretic Constraints for Continual Vision-Language-Action Alignment
Libang Zhao, Qixin Zeng, Hongyin Zhang +1
When deployed in open-ended robotic environments, Vision--Language--Action (VLA) models need to continually acquire new skills, yet suffer from severe catastrophic forgetting. We o…
CMR: Contractive Mapping Embeddings for Robust Humanoid Locomotion on Unstructured Terrains
Qixin Zeng, Hongyin Zhang, Shangke Lyu +3
Robust disturbance rejection remains a longstanding challenge in humanoid locomotion, particularly on unstructured terrains where sensing is unreliable and model mismatch is pronou…
CRL-VLA: Continual Vision-Language-Action Learning
Qixin Zeng, Shuo Zhang, Hongyin Zhang +6
Lifelong learning is critical for embodied agents in open-world environments, where reinforcement learning fine-tuning has emerged as an important paradigm to enable Vision-Languag…