2 citations · 2 across the 8 of their papers we have counts for
9 papers
RSI-Router: Evolving Subtask-Level LLM Routing and Skills for Cost-Efficient Agents
Hao Li, Hangfan Zhang, Zhiyao Cui +5
Practical deployment of large language model (LLM) agents requires strong task performance at affordable inference cost. For long-horizon agentic tasks, this performance-cost trade…
AgentPanel: Toward a New Paradigm for Human--AI Collaboration in Exploring Scientific Questions
Zhiyao Cui, Qianyi Wang, Haoyang Yan +26
Identifying promising scientific ideas remains an important challenge in research practice. Researchers commonly rely on small-group discussions or one-to-one interactions with a s…
SKT: Skill-Use Training at Scale via Verified Synthetic Data Generation
Zelin Tan, Yiqun Zhang, Hao Li +11
Agent skills have become an important mechanism for equipping language-model agents with reusable procedural knowledge. However, providing skills alone does not guarantee that curr…
Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
Lei Bai, Zongsheng Cao, Yang Chen +50
We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We investigate agent-horizon scaling…
Design First, Code Later: Aesthetically Pleasing Template-Free Slides Generation
Zhiyao Cui, Chenxu Wang, Shuyue Hu +4
Producing presentation slides automatically entails coordinating narrative structure with page-level graphic design under strict spatial constraints. For such structured multimodal…
Organizing, Orchestrating, and Benchmarking Agent Skills at Ecosystem Scale
Hao Li, Chunjiang Mu, Jianhao Chen +5
The rapid proliferation of Claude agent skills has raised the central question of how to effectively leverage, manage, and scale the agent skill ecosystem. In this paper, we propos…
PerPilot: Personalizing VLM-based Mobile Agents via Memory and Exploration
Xin Wang, Zhiyao Cui, Hao Li +10
Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with perso…
Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity
Hangfan Zhang, Zhiyao Cui, Jianhao Chen +5
Multi-agent debate (MAD) has gained significant attention as a promising line of research to improve the factual accuracy and reasoning capabilities of large language models (LLMs)…
Emergence of Social Norms in Generative Agent Societies: Principles and Architecture
Siyue Ren, Zhiyao Cui, Ruiqi Song +2
Social norms play a crucial role in guiding agents towards understanding and adhering to standards of behavior, thus reducing social conflicts within multi-agent systems (MASs). Ho…