6 citations · 10 across the 7 of their papers we have counts for
9 papers
IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems
A. Jian Yang, An Huang, Bo Dan +173
We present IQuest-Q1, a sparse Mixture-of-Experts (MoE) agentic foundation model with 320B total parameters (15B activated). IQuest-Q1 is developed through a three-stage process: (…
AutoGUI-v2: A Comprehensive Multi-Modal GUI Functionality Understanding Benchmark
Hongxin Li, Xiping Wang, Jingran Su +4
Autonomous agents capable of navigating Graphical User Interfaces (GUIs) hold the potential to revolutionize digital productivity. However, achieving true digital autonomy extends…
GoClick: Lightweight Element Grounding Model for Autonomous GUI Interaction
Hongxin Li, Yuntao Chen, Zhaoxiang Zhang
Graphical User Interface (GUI) element grounding (precisely locating elements on screenshots based on natural language instructions) is fundamental for agents interacting with GUIs…
UIPro: Unleashing Superior Interaction Capability For GUI Agents
Hongxin Li, Jingran Su, Jingfan Chen +4
Building autonomous agents that perceive and operate graphical user interfaces (GUIs) like humans has long been a vision in the field of artificial intelligence. Central to these a…
AutoGUI: Scaling GUI Grounding with Automatic Functionality Annotations from LLMs
Hongxin Li, Jingfan Chen, Jingran Su +3
User interface understanding with vision-language models (VLMs) has received much attention due to its potential for enhancing software automation. However, existing datasets used…
MemoNav: Working Memory Model for Visual Navigation
Hongxin Li, Zeyu Wang, Xu Yang +3
Image-goal navigation is a challenging task that requires an agent to navigate to a goal indicated by an image in unfamiliar environments. Existing methods utilizing diverse scene…
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving
Yuqi Wang, Jiawei He, Lue Fan +3
In autonomous driving, predicting future events in advance and evaluating the foreseeable risks empowers autonomous vehicles to better plan their actions, enhancing safety and effi…
SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models
Hongxin Li, Jingran Su, Yuntao Chen +2
Computer end users have spent billions of hours completing daily tasks like tabular data processing and project timeline scheduling. Most of these tasks are repetitive and error-pr…
MemoNav: Selecting Informative Memories for Visual Navigation
Hongxin Li, Xu Yang, Yuran Yang +2
Image-goal navigation is a challenging task, as it requires the agent to navigate to a target indicated by an image in a previously unseen scene. Current methods introduce diverse…