activity
20242026
most citedA Survey on the Optimization of Large Language Model-based Agents

15 citations · 16 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

ERR+: Sequential Entropy Resolution for Efficient and Decisive LLM Reasoning

Xin Jiang, Minhao Wang, Wen Wu +4

Large reasoning models achieve strong performance on complex tasks by generating extended chain-of-thought (CoT) traces via reinforcement learning with verifiable rewards (RLVR). W…

cs.CR2026

(A)I Sees What You Don't: Exploiting New Attack Surfaces in Third-Party Mobile Agents

Zidong Zhang, Zhentao Xie, Wenrui Diao +1

Third-party mobile agents powered by Vision-Language Models (VLMs) have emerged as a promising paradigm for automating smartphone interactions. These agents act as high-privilege d…

cs.CR2026

Mini-Programs, Mega-Problems: Unveiling OAuth-based Authentication Misuses in Mini-Programs via Dynamic Analysis

Zidong Zhang, Zhentao Xie, Lingyun Ying +4

Mini-programs have become a dominant paradigm for lightweight application deployment within super apps such as WeChat. To support seamless integration, super apps provide OAuth mec…

cs.AI2025

RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual Compensation

Zhentao Xie, Chengcheng Han, Jinxin Shi +4

Although multi-agent systems based on large language models show strong capabilities on multiple tasks, they are still limited by high computational overhead, information loss, and…

cs.AI2025★ 15 cited

A Survey on the Optimization of Large Language Model-based Agents

Shangheng Du, Jiabao Zhao, Jinxin Shi +4

With the rapid development of Large Language Models (LLMs), LLM-based agents have been widely adopted in various fields, becoming essential for autonomous decision-making and inter…

cs.CL2024★ 1 cited

MindScope: Exploring cognitive biases in large language models through Multi-Agent Systems

Zhentao Xie, Jiabao Zhao, Yilei Wang +4

Detecting cognitive biases in large language models (LLMs) is a fascinating task that aims to probe the existing cognitive biases within these models. Current methods for detecting…