1 citations · 2 across the 7 of their papers we have counts for
7 papers
Darwin Mobile Agent: A Roadmap for Self-Evolution
Daniel Beechey, Derek Yuen, Jianheng Liu +5
The goal of artificial intelligence is to create agents capable of general, adaptive behaviour in open-ended environments. Guided by the "Bitter Lesson", we argue that the most eff…
K^2-Agent: Co-Evolving Know-What and Know-How for Hierarchical Mobile Device Control
Zhe Wu, Donglin Mo, Hongjin Lu +7
Existing mobile device control agents often perform poorly when solving complex tasks requiring long-horizon planning and precise operations, typically due to a lack of relevant ta…
Beyond Syntax: Action Semantics Learning for App Agents
Bohan Tang, Dezhao Luo, Jianheng Liu +5
The recent development of Large Language Models (LLMs) enables the rise of App agents that interpret user intent and operate smartphone Apps through actions such as clicking and sc…
Advancing Autonomous VLM Agents via Variational Subgoal-Conditioned Reinforcement Learning
Qingyuan Wu, Jianheng Liu, Jianye Hao +2
State-of-the-art (SOTA) reinforcement learning (RL) methods have enabled vision-language model (VLM) agents to learn from interaction with online environments without human supervi…
Detect an Object At Once without Fine-tuning
Junyu Hao, Jianheng Liu, Yongjia Zhao +5
When presented with one or a few photos of a previously unseen object, humans can instantly recognize it in different scenes. Although the human brain mechanism behind this phenome…
OCMDP: Observation-Constrained Markov Decision Process
Taiyi Wang, Jianheng Liu, Bryan Lee +2
In many practical applications, decision-making processes must balance the costs of acquiring information with the benefits it provides. Traditional control systems often assume fu…