12 papers · 1 filter
AOHP: An Open-Source OS-Level Agent Harness for Personalized, Efficient and Secure Interaction
Shanhui Zhao, Jiacheng Liu, Guohong Liu +13
AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data s…
ScaleWoB: Guiding GUI Agents with Coding Agents via Large-Scale Environmental Synthesis
Guohong Liu, Jialei Ye, Pengzhi Gao +4
GUI agents powered by large language models are advancing rapidly, creating urgent needs for evaluation and training based on realistic environments. However, directly doing so in…
Joint Agent Memory and Exploration Learning via Novelty Signals
Shizuo Tian, Xiaohong Weng, Rui Kong +9
In open-ended environments, exploration is fundamental for autonomous agents, yet current language model agents struggle with this. Effective exploration requires memory, but retai…
AgentProg: Empowering Long-Horizon GUI Agents with Program-Guided Context Management
Shizuo Tian, Hao Wen, Yuxuan Chen +6
The rapid development of mobile GUI agents has stimulated growing research interest in long-horizon task automation. However, building agents for these tasks faces a critical bottl…
GRAIL:Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning
Ge Chang, Jinbo Su, Jiacheng Liu +7
Large Language Models (LLMs) integrated with Retrieval-Augmented Generation (RAG) techniques have exhibited remarkable performance across a wide range of domains. However, existing…
ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
Gaole Dai, Shiqi Jiang, Ting Cao +5
Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods struggle to generalize to GUI agents,…