collaborators

5 papers

cs.AI2026

DynaDebate: Breaking Homogeneity in Multi-Agent Debate with Dynamic Path Generation

Zhenghao Li, Zhi Zheng, Wei Chen +4

Recent years have witnessed the rapid development of Large Language Model-based Multi-Agent Systems (MAS), which excel at collaborative decision-making and complex problem-solving.…

cs.AI2026

Defending LLM-based Multi-Agent Systems Against Cooperative Attacks with Sentence-Level Rectification

Yaoyang Luo, Zhi Zheng, Ziwei Zhao +5

Recent years have witnessed the rapid development of Large Language Model-based Multi-Agent Systems (MAS), which excel at collaborative decision-making and complex problem-solving.…

cs.CL2026

Towards Fair and Comprehensive Evaluation of Routers in Collaborative LLM Systems

Wanxing Wu, He Zhu, Yixia Li +7

Large language models (LLMs) have achieved success, but cost and privacy constraints necessitate deploying smaller models locally while offloading complex queries to cloud-based mo…

cs.CV2026

WorldVQA: Measuring Atomic World Knowledge in Multimodal Large Language Models

Runjie Zhou, Youbo Shao, Haoyu Lu +16

We introduce WorldVQA, a benchmark designed to evaluate the atomic visual world knowledge of Multimodal Large Language Models (MLLMs). Unlike current evaluations, which often confl…

cs.CL2025

ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation

Chenchen Zhang, Yuhang Li, Can Xu +17

The generative capabilities of Large Language Models (LLMs) are rapidly expanding from static code to dynamic, interactive visual artifacts. This progress is bottlenecked by a crit…