5 papers
How AI Agents Follow the Herd of AI? Network Effects, History, and Machine Optimism
Yu Liu, Wenwen Li, Yifan Dou +1
Understanding decision-making in multi-AI-agent frameworks is crucial for analyzing strategic interactions in network-effect-driven contexts. This study investigates how AI agents…
LLM-Friendly Knowledge Representation for Customer Support
Hanchen Su, Wei Luo, Wei Han +5
We propose a practical approach by integrating Large Language Models (LLMs) with a framework designed to navigate the complexities of Airbnb customer support operations. In this pa…
Agent-in-the-Loop: A Data Flywheel for Continuous Improvement in LLM-based Customer Support
Cen Mia Zhao, Tiantian Zhang, Hanchen Su +8
We introduce an Agent-in-the-Loop (AITL) framework that implements a continuous data flywheel for iteratively improving an LLM-based customer support system. Unlike standard offlin…
When Machines Meet Each Other: Network Effects and the Strategic Role of History in Multi-Agent AI
Yu Liu, Wenwen Li, Yifan Dou +1
As artificial intelligence (AI) enters the agentic era, large language models (LLMs) are increasingly deployed as autonomous agents that interact with one another rather than opera…
MADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation
Mingjin Li, Yu Liu, Huayi Liu +4
We propose MADS (Multi-Agent Dialogue Simulation), a scalable framework for generating persuasive multi-turn dialogues via agent self-play. MADS employs three coordinated agents: U…