34 citations · 48 across the 16 of their papers we have counts for
7 papers · 1 filter
Factored Latent Action World Models
Zizhao Wang, Chang Shi, Jiaheng Hu +4
Learning latent actions from action-free video has emerged as a powerful paradigm for scaling up controllable world model learning. Latent actions provide a natural interface for u…
Adversarial Reinforcement Learning for Large Language Model Agent Safety
Zizhao Wang, Dingcheng Li, Vaishakh Keshava +4
Large Language Model (LLM) agents can leverage tools such as Google Search to complete complex tasks. However, this tool usage introduces the risk of indirect prompt injections, wh…
Dyn-O: Building Structured World Models with Object-Centric Representations
Zizhao Wang, Kaixin Wang, Li Zhao +2
World models aim to capture the dynamics of the environment, enabling agents to predict and plan for future states. In most scenarios of interest, the dynamics are highly centered…
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions
Zizhao Wang, Jiaheng Hu, Caleb Chuck +5
Unsupervised skill discovery carries the promise that an intelligent agent can learn reusable skills through autonomous, reward-free environment interaction. Existing unsupervised…
Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning
Jiaheng Hu, Zizhao Wang, Peter Stone +1
A hallmark of intelligent agents is the ability to learn reusable skills purely from unsupervised interaction with the environment. However, existing unsupervised skill discovery m…
ELDEN: Exploration via Local Dependencies
Jiaheng Hu, Zizhao Wang, Peter Stone +1
Tasks with large state space and sparse rewards present a longstanding challenge to reinforcement learning. In these tasks, an agent needs to explore the state space efficiently un…
Causal Dynamics Learning for Task-Independent State Abstraction
Zizhao Wang, Xuesu Xiao, Zifan Xu +2
Learning dynamics models accurately is an important goal for Model-Based Reinforcement Learning (MBRL), but most MBRL methods learn a dense dynamics model which is vulnerable to sp…