2 citations · 2 across the 9 of their papers we have counts for
9 papers
Towards Scalable Lightweight GUI Agents via Multi-role Orchestration
Ziwei Wang, Junjie Zheng, Leyang Yang +7
Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. While scaling both parameters an…
Generalizable Self-Evolving Memory for Automatic Prompt Optimization
Guanbao Liang, Yuanchen Bei, Sheng Zhou +5
Automatic prompt optimization is a promising approach for adapting large language models (LLMs) to downstream tasks, yet existing methods typically search for a specific prompt spe…
MaS-VQA: A Mask-and-Select Framework for Knowledge-Based Visual Question Answering
Xianwei Mao, Kai Ye, Sheng Zhou +4
Knowledge-based Visual Question Answering (KB-VQA) requires models to answer questions by integrating visual information with external knowledge. However, retrieved knowledge is of…
REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
Kai Ye, Xianwei Mao, Sheng Zhou +6
Knowledge-intensive Visual Question Answering (KI-VQA) frequently suffers from severe knowledge conflicts caused by the inherent limitations of open-domain retrieval. However, exis…
Towards Scalable Web Accessibility Audit with MLLMs as Copilots
Ming Gu, Ziwei Wang, Sicen Lai +3
Ensuring web accessibility is crucial for advancing social welfare, justice, and equality in digital spaces, yet the vast majority of website user interfaces remain non-compliant,…
Leveraging LLM Agents for Automated Video Game Testing
Chengjia Wang, Lanling Tang, Ming Yuan +3
Testing MMORPGs (Massively Multiplayer Online Role-Playing Games) is a critical yet labor-intensive task in game development due to their complexity and frequent updating nature. T…
PG-Agent: An Agent Powered by Page Graph
Weizhi Chen, Ziwei Wang, Leyang Yang +5
Graphical User Interface (GUI) agents possess significant commercial and social value, and GUI agents powered by advanced multimodal large language models (MLLMs) have demonstrated…
Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities
Yuanchen Bei, Weizhi Zhang, Siwen Wang +10
AI agents have experienced a paradigm shift, from early dominance by reinforcement learning (RL) to the rise of agents powered by large language models (LLMs), and now further adva…
Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap
Weizhi Zhang, Yuanchen Bei, Liangwei Yang +15
Cold-start problem is one of the long-standing challenges in recommender systems, focusing on accurately modeling new or interaction-limited users or items to provide better recomm…