5 papers · 1 filter
GDLAM: Group-Disentangled Latent Action Model for Highly Disentangled Embodied Pretraining
Jiarui Yang, Jiawei Li, Jiale Zhang +5
Latent action models (LAMs) learn action-related representations from action-free videos via self-supervised future prediction, offering a scalable paradigm for embodied intelligen…
In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use
Jiarui Yang, Wen Huang, Jiale Zhang +2
Vision-Language-Action (VLA) models have become the dominant recipe for generalist manipulation, yet they are almost universally trained by behavior cloning: a policy imitates expe…
LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models
Jiarui Yang, Jiale Zhange, Jiawei Li +5
World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied intelligence remains limited by…
ARBOR: Online Process Rewards via a Reusable Rubric Buffer for Search Agents
Zheng Liu, Longxiang Zhang, Xintong Wang +8
LLM-based search agents are trained predominantly with outcome-only reward, leaving the search process itself unsupervised. This signal degenerates on outcome-homogeneous groups wh…
3ViewSense: Spatial and Mental Perspective Reasoning from Orthographic Views in Vision-Language Models
Shaoxiong Zhan, Yanlin Lai, Zheng Liu +6
Current Large Language Models have achieved Olympiad-level logic, yet Vision-Language Models paradoxically falter on elementary spatial tasks like block counting. This capability m…