17 papers
WCM: A World Critic Model for Vision-Language-Action Reinforcement Learning
Senyu Fei, Xiaopeng Yu, Siyin Wang +3
Reinforcement learning (RL) post-training of Vision-Language-Action (VLA) models has shown strong promise for robotic manipulation. Among RL methods, critic-based approaches rely o…
HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control
Li Ji, Siyin Wang, Pengfang Qian +5
Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and reasoning due to their reliance…
In-Context World Modeling for Robotic Control
Siyin Wang, Junhao Shi, Senyu Fei +4
Modern Vision-Language-Action (VLA) models often fail to generalize to novel setups, such as altered camera viewpoints or robot morphologies, because they are typically conditioned…
Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
Junhao Shi, Siyin Wang, Xiaopeng Yu +3
Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions, and actions that are costly t…
Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy
Junhao Shi, Zezheng Huai, Siyin Wang +7
Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT) and physical (manipulation, na…
Augmenting Dysarthric Speech Severity Assessment with MOS Supervision
Kaimeng Jia, Minzhu Tu, Zengrui Jin +2
Dysarthria is a speech disorder marked by reduced intelligibility and communicative effectiveness. Automatic utterance-level assessment of dysarthric speech can support scalable sp…