9 papers
Interactive Reward Agent: GUI Task Evaluation via Environment-State Verification
Chenrui Shi, Yuwei Wu, Yang Liu +5
Graphical user interface task evaluation aims to determine whether a GUI agent has successfully completed a user instruction. Automated GUI task evaluation has received increasing…
Beyond Sequential Interaction: Benchmarking Parallel Execution and Coordination for GUI Agents
Zedong Yu, Qianxing Li, Zhi Gao +8
Graphical user interface (GUI) agents are systems powered by large multimodal models (LMMs). They perceive screen state and execute user instructions through GUI actions such as cl…
Benchmarking and Improving GUI Agents in High-Dynamic Environments
Enqi Liu, Liyuan Pan, Zhi Gao +5
Recent advancements in Graphical User Interface (GUI) agents have predominantly focused on training paradigms like supervised fine-tuning (SFT) and reinforcement learning (RL). How…
GUIDE: Resolving Domain Bias in GUI Agents through Real-Time Web Video Retrieval and Plug-and-Play Annotation
Rui Xie, Zhi Gao, Chenrui Shi +3
Large vision-language models have endowed GUI agents with strong general capabilities for interface understanding and interaction. However, due to insufficient exposure to domain-s…
GUI Knowledge Bench: Revealing the Knowledge Gap of VLMs in GUI Tasks
Chenrui Shi, Zedong Yu, Zhi Gao +7
Vision language models (VLMs) have advanced graphical user interface (GUI) task automation but still lag behind humans. We hypothesize this gap stems from missing core GUI knowledg…
Efficient Multi-turn RL for GUI Agents via Decoupled Training and Adaptive Data Curation
Pengxiang Li, Zechen Hu, Zirui Shang +15
Vision-language model (VLM) based GUI agents show promise for automating complex desktop and mobile tasks, but face significant challenges in applying reinforcement learning (RL):…
Long-Horizon Visual Imitation Learning via Plan and Code Reflection
Quan Chen, Chenrui Shi, Qi Chen +6
Learning from long-horizon demonstrations with complex action sequences presents significant challenges for visual imitation learning, particularly in understanding temporal relati…
Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning
Pengxiang Li, Zhi Gao, Bofei Zhang +8
Multimodal agents, which integrate a controller e.g., a vision language model) with external tools, have demonstrated remarkable capabilities in tackling complex multimodal tasks.…
MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge
Yuntao Du, Kailin Jiang, Zhi Gao +4
Knowledge editing techniques have emerged as essential tools for updating the factual knowledge of large language models (LLMs) and multimodal models (LMMs), allowing them to corre…