3 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
Robust, Observable, and Evolvable Agentic Systems Engineering: A Principled Framework Validated via the Fairy GUI Agent
Jiazheng Sun, Ruimeng Yang, Xu Han +5
The Agentic Paradigm faces a significant Software Engineering Absence, yielding Agentic systems commonly lacking robustness, observability, and evolvability. To address these defic…
MCPWorld: A Unified Benchmarking Testbed for API, GUI, and Hybrid Computer Use Agents
Yunhe Yan, Shihe Wang, Jiajun Du +12
(M)LLM-powered computer use agents (CUA) are emerging as a transformative technique to automate human-computer interaction. However, existing CUA benchmarks predominantly target GU…
MiniCPM4: Ultra-Efficient LLMs on End Devices
MiniCPM Team, Chaojun Xiao, Yuxuan Li +80
This paper introduces MiniCPM4, a highly efficient large language model (LLM) designed explicitly for end-side devices. We achieve this efficiency through systematic innovation in…
OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model
Xingcheng Zhou, Xuyuan Han, Feng Yang +3
We present OpenDriveVLA, a Vision Language Action model designed for end-to-end autonomous driving, built upon open-source large language models. OpenDriveVLA generates spatially g…
LimSim Series: An Autonomous Driving Simulation Platform for Validation and Enhancement
Daocheng Fu, Naiting Zhong, Xu Han +5
Closed-loop simulation environments play a crucial role in the validation and enhancement of autonomous driving systems (ADS). However, certain challenges warrant significant atten…
LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models
Zengqi Peng, Yubin Wang, Xu Han +2
Recent advancements in reinforcement learning (RL) demonstrate the significant potential in autonomous driving. Despite this promise, challenges such as the manual design of reward…