4 papers
From Monolithic Blending to Agentic Orchestration: Dynamic Response for Conversational Assistants at Scale
Cen Mia Zhao, Peng Wang, Chuan Shi +6
Conversational assistants can blend retrieval, action selection, escalation, and wording in a single model path, or separate those roles. We report a production migration of a cust…
Beyond Prompts: Measuring and Optimizing LLM Tool-Agent Harnesses
Cen Mia Zhao, Haibo Ruan, Wenjie Chen +3
LLM tool agents can be improved without retraining by modifying the runtime harness around a fixed model: prompts, tool interfaces, middleware, state handling, and recovery logic.…
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…
Incremental Summarization for Customer Support via Progressive Note-Taking and Agent Feedback
Yisha Wu, Cen Mia Zhao, Yuanpei Cao +4
We introduce an incremental summarization system for customer support agents that intelligently determines when to generate concise bullet notes during conversations, reducing agen…