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20222026
most citedHierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality

18 citations · 36 across the 21 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.AI2024

MRJ-Agent: An Effective Jailbreak Agent for Multi-Round Dialogue

Fengxiang Wang, Ranjie Duan, Peng Xiao +9

Large Language Models (LLMs) demonstrate outstanding performance in their reservoir of knowledge and understanding capabilities, but they have also been shown to be prone to illega…

cs.LG2024★ 1 cited

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…

cs.LG2024

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…

cs.LG2024

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…

cs.LG2024

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…