Author

Jiakang Yuan

Fudan University

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#artificial intelligence Preprint Oct 2026

DHCG: Dynamic Construction of Hierarchical Collaboration Graphs for LLM-Based Multi-Agent Reasoning

LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orchestration of agent systems has become an important research direction. However, existing methods suffer from limited composition, misaligned dependencies, and inflexibl...

Jie Ren, Jiakang Yuan, Chen-Yu Huang et al. · 0 citations

#natural language process... Review Sep 2026

RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents

This work introduces RecreationWorld, a five-platform framework built around recreation: given a running reference, an agent must discover its behavior and build a faithful implementation with no prescribed workflow, and introduces RecreationBench, comprising 250 diverse tasks across domains and platforms.

Shuai Bai, Jia-Yong Deng, Si-Cheng Fan et al. · 1 citation

#natural language process... Review Sep 2026

Efficient GUI Agents: A Systems Survey of Observation, Memory, Action, and Runtime Optimization

This survey studies efficient GUI agents through an end-to-end systems lens that preserves the current technical axes of observation efficiency, context and memory efficiency, action efficiency, and planner-side/system efficiency.

Bizhe Bai, Jiakang Yuan, Hong-Zhou Wu et al. · 0 citations

#artificial intelligence Conference Jan 2026

Controllable Memory Usage: Balancing Anchoring and Innovation in Long-Term Human-Agent Interaction

This work shows that an agent's reliance on memory can be modeled as an explicit and user-controllable dimension, and proposes a framework that allows users to dynamically regulate memory reliance, ranging from a fresh-start mode that promotes innovation to a high-fidelity mode that closely follows interaction history.

Mu-Zhao Tian, Zi-Su Huang, Xiaohua Wang et al. · Annual Meeting of the Associ... · 0 citations

Preprint Aug 2026

Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System

UAV-MAS is proposed, a training-free multi-agent system for MLLM-based UAV aerial image understanding and reasoning, comprising a Domain-Specific Perception Engine that routes queries to task-appropriate visual tools, a Context-Aware Iterative Refinement module (CAIR) that validates intermediate reasoning to curb error...

Hao-Yu Zhang, Shuoxun Zhang, Peng Ye et al. · 0 citations

Preprint Aug 2026

AeroGround: A Comprehensive Benchmark for Aerial-Ground Collaborative Reasoning

By systematically revealing the strengths and limitations of existing models in aerial-ground collaborative reasoning, AeroGround provides a foundation for developing more capable aerial-ground collaborative embodied intelligence systems.

Shenghong Yi, Lin Zhang, Muzian Li et al. · 0 citations