activity
20242026
most citedThe Athenian Academy: A Seven-Layer Architecture Model for Multi-Agent Systems

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Self-Augmented Mixture-of-Experts for QoS Prediction

Kecheng Cai, Chao Peng, Chenyang Xu +4

Quality of Service (QoS) prediction is one of the most fundamental problems in service computing and personalized recommendation. In the problem, there is a set of users and servic…

cs.SE2026

Deploy-Master: Automating the Deployment of 50,000+ Agent-Ready Scientific Tools in One Day

Yi Wang, Zhenting Huang, Zhaohan Ding +6

Open-source scientific software is abundant, yet most tools remain difficult to compile, configure, and reuse, sustaining a small-workshop mode of scientific computing. This deploy…

math.ST2025

Sharp comparisons between sliced and standard -Wasserstein distances

Guillaume Carlier, Alessio Figalli, Quentin Mérigot +1

Sliced Wasserstein distances are widely used in practice as a computationally efficient alternative to Wasserstein distances in high dimensions. In this paper, motivated by theoret…

cs.LG2025

Intern-S1: A Scientific Multimodal Foundation Model

Lei Bai, Zhongrui Cai, Yuhang Cao +173

In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…

cs.MA2025

IndoorWorld: Integrating Physical Task Solving and Social Simulation in A Heterogeneous Multi-Agent Environment

Dekun Wu, Frederik Brudy, Bang Liu +1

Virtual environments are essential to AI agent research. Existing environments for LLM agent research typically focus on either physical task solving or social simulation, with the…

cs.MA20251 cited

The Athenian Academy: A Seven-Layer Architecture Model for Multi-Agent Systems

Lidong Zhai, Zhijie Qiu, Lvyang Zhang +5

This paper proposes the "Academy of Athens" multi-agent seven-layer framework, aimed at systematically addressing challenges in multi-agent systems (MAS) within artificial intellig…