Papers by Kehan Chen

2 papers
ChatMap: Mining Human Thought Processes for Customer Service Chatbots via Multi-Agent Collaboration (2025.findings-acl)

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Challenge: Existing methods for enhancing dialogue performance rely on summarizing behavior . e-commerce chatbots need to align their dialogue strategies with human behavior to achieve coherent, human-like conversations with customers.
Approach: They propose a method to extract core patterns from dialogue data and integrate them into models by mining service thought processes using a multi-agent aPproach.
Outcome: The proposed method outperforms manual methods and outperfies baselines on Taobao in China.
Meta-Reflection: A Feedback-Free Reflection Learning Framework (2025.acl-long)

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Challenge: Existing approaches to improve large language models' ability to understand and reason are limited by external feedback.
Approach: They propose a feedback-free reflection mechanism that requires only a single inference pass without external feedback.
Outcome: The proposed method is based on an industrial e-commerce benchmark and public datasets.

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