Papers by Feifan Yan

2 papers
Seamlessly Integrating Factual Information and Social Content with Persuasive Dialogue (2022.aacl-main)

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Challenge: Persuasive dialogue systems are designed for chatbots to communicate with and influence users with specific goals.
Approach: They propose a modular dialogue system framework that integrates factual information and social content into persuasive dialogues.
Outcome: The proposed framework is generalizable to any dialogue tasks that have mixed social and task contents.
LEGOEval: An Open-Source Toolkit for Dialogue System Evaluation via Crowdsourcing (2021.acl-demo)

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Challenge: Currently, researchers use automatic metrics and human evaluation to evaluate dialogue systems.
Approach: They propose to use a Python API to easily evaluate dialogue systems using Amazon Mechanical Turk.
Outcome: The open-source toolkit provides a fast, consistent method for reproducing human evaluation results.

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