Papers by Kunfeng Lai

3 papers
Make Templates Smarter: A Template Based Data2Text System Powered by Text Stitch Model (2020.findings-emnlp)

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Challenge: Neural network based data2text models drop or modify information in inputs and it is hard to control the generated contents.
Approach: They propose a template-based data2text system powered by a text stitch model that automatically stitches adjacent template units.
Outcome: The proposed system outperforms template-based systems in fidelity and human involvement on a benchmark dataset.
Task-Completion Dialogue Policy Learning via Monte Carlo Tree Search with Dueling Network (2020.emnlp-main)

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Challenge: Existing models of reinforcement learning use background planning and may suffer from low-quality simulated experiences.
Approach: They propose a Monte Carlo Tree Search with Double-q Dueling network framework for task-completion dialogue policy learning.
Outcome: The proposed method outperforms the previous model-based reinforcement learning methods and is robust to simulation errors.
Matching Article Pairs with Graphical Decomposition and Convolutions (P19-1)

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Challenge: Existing methods for matching sentence pairs do not perform well in longer documents . Existing approaches for matching sentences do not work in longer document understanding tasks .
Approach: They propose to model article pairs by comparing sentences that enclose same concept vertex . they propose to use a concept interaction graph to match articles by encoding sentences .
Outcome: The proposed methods show significant improvements over existing methods . the proposed datasets consist of 30K pairs of breaking news articles .

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