5 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
Interaction Latents as Actions for Contact-Rich Manipulation
Yuhang Zheng, Yujie Zang, Yuchen Liu +9
Contact-rich manipulation requires robots to coordinate not only where to move, but also how contact and force should evolve throughout an interaction. Yet most robot policies repr…
KineWorld: Action-Induced Transport Fields for Embodied World Modeling
Ziying Song, Yuchen Liu, Zhuoran Xu +6
Embodied world models predict the visual consequences of candidate actions before execution. However, existing action-conditioned world models often adopt uniformly weighted visual…
Not All History Helps: Velocity-Aware Selective Memory for Long-Horizon End-to-End Autonomous Driving
Yuchen Liu, Ziying Song, Shengkai Zhang +6
Reliable long-horizon planning remains a key challenge in end-to-end autonomous driving. By accounting for future motion evolution and potential consequences, it provides forward-l…
Agentic Open RAN: A Deterministic and Auditable Framework for Intent-Driven Radio Control
Hengxu Li, Dongkuan Xu, Mingzhe Chen +1
Large language models (LLMs) open new possibilities for agentic control in Open RAN, allowing operators to express intents in natural language while delegating low-level execution…
Weakly-supervised Learning for Physics-informed Neural Motion Planning via Sparse Roadmap
Ruiqi Ni, Yuchen Liu, Ahmed H. Qureshi
The motion planning problem requires finding a collision-free path between start and goal configurations in high-dimensional, cluttered spaces. Recent learning-based methods offer…