5 citations · 11 across the 11 of their papers we have counts for
5 papers · 1 filter
PrefO2O: Zero-Shot Preference-Based Reinforcement Learning via Offline-to-Online Latent Preference Transfer
Ruiqi Wang, Dezhong Zhao, Xuesu Xiao +3
Preference-based reinforcement learning (PbRL) has emerged as a promising paradigm for learning robot behaviors aligned with human intent. However, its scalability is fundamentally…
Does Continual Imitation Learning Remain Grounded? A Language-Perturbed Benchmark for Robotic Task Retention
Siddeshwar Raghavan, Ziqin Yuan, Fengqing Zhu +1
Continual imitation learning evaluates whether a robot can learn new knowledge without forgetting previously learned skills. However, retaining task performance does not ensure the…
Communication-Aware Heterogeneous Graph Learning for Decentralized Multi-Human Multi-Robot Task Allocation
Ziqin Yuan, Ruiqi Wang, Baijian Yang +1
Multi-human multi-robot (MH-MR) teams combine robotic autonomy with human expertise, but effective task allocation requires coordinating scarce, dynamically available human support…
PrefMoE: Robust Preference Modeling with Mixture-of-Experts Reward Learning
Ziqin Yuan, Ruiqi Wang, Dezhong Zhao +2
Preference-based reinforcement learning offers a scalable alternative to manual reward engineering by learning reward structures from comparative feedback. However, large-scale pre…
Pre-Execution Safety Gate & Task Safety Contracts for LLM-Controlled Robot Systems
Ike Obi, Vishnunandan L. N. Venkatesh, Weizheng Wang +5
Large Language Models (LLMs) are increasingly used to convert task commands into robot-executable code, however this pipeline lacks validation gates to detect unsafe and defective…