3 papers indexed
Junlong Xiao, Yaoqiang Pan, Xuan Zhang, Michael Yu Wang, Chao Chen
Soft robots have seen widespread adoption in interactive tasks due to their inherent compliance and adaptability. However, these advantages often come at the cost of stability, posing challenges in a dynamic environment. This limitation is especially critical in soft grippers, wh…
Xuan Zhang, Wenxuan Zhang, See-Kiong Ng, Yang Deng
World models offer a principled way to equip long-horizon LLM agents with foresight: predictions of action consequences before execution. However, unreliable foresight can be ignored, misused, or even degrade downstream decision-making. In this paper, we introduce WorldEvolver, a…
Xuan Zhang, Zhijian Zhou, Lingfeng Qiao, Yulei Qin, Ke Li, Xing Sun, et al.
Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-horizon tasks. Unlike humans who employ "what-if" reasoning to evaluate potential plans before commitment, standard agents lack an…