18 citations · 21 across the 2 of their papers we have counts for
11 papers
Advancing Prompt-Based Methods for Replay-Independent General Continual Learning
Zhiqi Kang, Liyuan Wang, Xingxing Zhang +1
General continual learning (GCL) is a broad concept to describe real-world continual learning (CL) problems, which are often characterized by online data streams without distinct t…
ManiBox: Enhancing Embodied Spatial Generalization via Scalable Simulation Data Generations
Hengkai Tan, Xuezhou Xu, Chengyang Ying +7
Embodied agents require robust spatial intelligence to execute precise real-world manipulations. However, this remains a significant challenge, as current methods often struggle to…
HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning
Liyuan Wang, Jingyi Xie, Xingxing Zhang +2
The deployment of pre-trained models (PTMs) has greatly advanced the field of continual learning (CL), enabling positive knowledge transfer and resilience to catastrophic forgettin…
Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
Hengkai Tan, Songming Liu, Kai Ma +4
Transformer has shown promise in reinforcement learning to model time-varying features for obtaining generalized low-level robot policies on diverse robotics datasets in embodied l…
PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
Chengyang Ying, Zhongkai Hao, Xinning Zhou +4
Designing generalizable agents capable of adapting to diverse embodiments has achieved significant attention in Reinforcement Learning (RL), which is critical for deploying RL agen…
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction Alignment
Kanglei Zhou, Junlin Li, Ruizhi Cai +3
Action Quality Assessment (AQA) is pivotal for quantifying actions across domains like sports and medical care. Existing methods often rely on pre-trained backbones from large-scal…