2 citations · 2 across the 7 of their papers we have counts for
8 papers
Web2BigTable: A Bi-Level Multi-Agent LLM System for Internet-Scale Information Search and Extraction
Yuxuan Huang, Yihang Chen, Zhiyuan He +6
Agentic web search increasingly faces two distinct demands: deep reasoning over a single target, and structured aggregation across many entities and heterogeneous sources. Current…
ProMMSearchAgent: A Generalizable Multimodal Search Agent Trained with Process-Oriented Rewards
Wentao Yan, Shengqin Wang, Huichi Zhou +4
Training multimodal agents via reinforcement learning for knowledge-intensive visual reasoning is fundamentally hindered by the extreme sparsity of outcome-based supervision and th…
DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents
Shengqin Wang, Wentao Yan, Huichi Zhou +4
Agentic multimodal models have garnered significant attention for their ability to leverage external tools to tackle complex tasks. However, it is observed that such agents often m…
EE-MCP: Self-Evolving MCP-GUI Agents via Automated Environment Generation and Experience Learning
Tiantian He, Yihang Chen, Keyue Jiang +4
Computer-use agents that combine GUI interaction with structured API calls via the Model Context Protocol (MCP) show promise for automating software tasks. However, existing approa…
Memento-Skills: Let Agents Design Agents
Huichi Zhou, Siyuan Guo, Anjie Liu +14
We introduce \emph{Memento-Skills}, a generalist, continually-learnable LLM agent system that functions as an \emph{agent-designing agent}: it autonomously constructs, adapts, and…
PerPilot: Personalizing VLM-based Mobile Agents via Memory and Exploration
Xin Wang, Zhiyao Cui, Hao Li +10
Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with perso…