7 papers
Self-Supervised Skill Optimization
Siran Peng, Cuiyu Yang, Tianyu Fu +9
Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized with ground-truth (GT) feed…
Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning
Jian Hu, Huiying Li, Hao Zhang +8
Agentic reinforcement learning requires rapid experimentation with agents and learning algorithms, yet large policies and long, multimodal trajectories demand substantial distribut…
TongSIM: A General Platform for Simulating Intelligent Machines
Zhe Sun, Kunlun Wu, Chuanjian Fu +24
As artificial intelligence (AI) rapidly advances, especially in multimodal large language models (MLLMs), research focus is shifting from single-modality text processing to the mor…
CollabVLA: Self-Reflective Vision-Language-Action Model Dreaming Together with Human
Nan Sun, Yongchang Li, Chenxu Wang +2
In this work, we present CollabVLA, a self-reflective vision-language-action framework that transforms a standard visuomotor policy into a collaborative assistant. CollabVLA tackle…
Body Discovery of Embodied AI
Zhe Sun, Pengfei Tian, Xiaozhu Hu +3
In the pursuit of realizing artificial general intelligence (AGI), the importance of embodied artificial intelligence (AI) becomes increasingly apparent. Following this trend, rese…
Bounding-Box Inference for Error-Aware Model-Based Reinforcement Learning
Erin J. Talvitie, Zilei Shao, Huiying Li +4
In model-based reinforcement learning, simulated experiences from the learned model are often treated as equivalent to experience from the real environment. However, when the model…
Question Answering Over Spatio-Temporal Knowledge Graph
Xinbang Dai, Huiying Li, Nan Hu +4
Spatio-temporal knowledge graphs (STKGs) enhance traditional KGs by integrating temporal and spatial annotations, enabling precise reasoning over questions with spatio-temporal dep…