9 citations · 54 across the 33 of their papers we have counts for
7 papers · 1 filter
From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents
Haipeng Ding, Yuexiang Xie, Zhewei Wei +2
Tool utilization enables Large Language Model (LLM) agents to interact with the real world and resolve complex tasks. However, existing agent frameworks predominantly rely on stati…
Learning Agent-Compatible Context Management for Long-Horizon Tasks
Lu Yi, Runlin Lei, Liuyi Yao +6
LLM agents increasingly face long-horizon tasks such as web search and deep research in real-world applications, where accumulated context can cause long-context degradation and re…
IntentRL: Training Proactive User-intent Agents for Open-ended Deep Research via Reinforcement Learning
Haohao Luo, Zexi Li, Yuexiang Xie +3
Deep Research (DR) agents extend Large Language Models (LLMs) beyond parametric knowledge by autonomously retrieving and synthesizing evidence from large web corpora into long-form…
Enhancing Multimodal Retrieval via Complementary Information Extraction and Alignment
Delong Zeng, Yuexiang Xie, Yaliang Li +1
Multimodal retrieval has emerged as a promising yet challenging research direction in recent years. Most existing studies in multimodal retrieval focus on capturing information in…
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Dawei Gao, Zitao Li, Yuexiang Xie +20
Driven by rapid advancements of Large Language Models (LLMs), agents are empowered to combine intrinsic knowledge with dynamic tool use, greatly enhancing their capacity to address…
KIMAs: A Configurable Knowledge Integrated Multi-Agent System
Zitao Li, Fei Wei, Yuexiang Xie +6
Knowledge-intensive conversations supported by large language models (LLMs) have become one of the most popular and helpful applications that can assist people in different aspects…
Agent-Oriented Planning in Multi-Agent Systems
Ao Li, Yuexiang Xie, Songze Li +3
Through the collaboration of multiple LLM-empowered agents possessing diverse expertise and tools, multi-agent systems achieve impressive progress in solving real-world problems. G…