Papers by Yajiao Wang

2 papers
One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems (2023.acl-long)

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Challenge: Recent studies have found that Task-oriented Dialogue systems can be more suitable for human users.
Approach: They propose a framework to optimize ToD systems by leveraging Multiple User SimulaTors.
Outcome: The proposed framework improves performance on multiWOZ with human evaluations and automatic evaluations.
SudokuFill: A Multi-Agent Progressive Filling Framework for Document-Level Scientific Information Extraction (2026.findings-acl)

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Challenge: Scientific information extraction (SciIE) is a key bottleneck for turning unstructured papers into computable knowledge bases.
Approach: They propose a scientific information extraction framework that solves a Sudoku problem as a progressive filling problem.
Outcome: The proposed framework outperforms the GPT-4o model on a document-level adjuvant dataset.

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