20 citations · 69 across the 16 of their papers we have counts for
5 papers · 1 filter
JuryFlow: Disagreement-Guided Human-in-the-Loop Multi-Agent Evaluation
Mufeng Yang, Junwei Yu, Yepeng Ding
Large language models (LLMs) are increasingly deployed as automated judges for AI-generated content, yet a single judge is unreliable and even a panel of judges leaves a hard resid…
Conversational Capture: A Trajectory-Level Framework for Evaluating Generative Engine Optimization in Multi-turn Human-Agent Interaction
Junwei Yu, Jieyu Zhou, Mufeng Yang +2
Generative Engine Optimization (GEO) shapes content to increase its likelihood of being cited by answer engines built on retrieval-augmented large language models. GEO is typically…
Eco3S: Complex Socio-Economic System Simulation via Agent-Based Models
Shaopeng Wei, Yufei Cheng, Wenxi Sun +3
The rapid development of large language models (LLMs) has renewed interest in agent-based modeling (ABM). However, current LLM-based ABM research faces several key challenges: mode…
NetAgentBench: A State-Centric Benchmark for Evaluating Agentic Network Configuration
Ahmed Twabi, Yepeng Ding, Tohru Kondo
As agentic network management gains popularity, there is a critical need for evaluation frameworks that transcend static, one-shot testing. To address this, we introduce NetAgentBe…
Structural Feature Engineering for Generative Engine Optimization: How Content Structure Shapes Citation Behavior
Junwei Yu, Mufeng Yang, Yepeng Ding +1
The proliferation of AI-powered search engines has shifted information discovery from traditional link-based retrieval to direct answer generation with selective source citation, c…