Tuan Manh Lai — accepted AI-conference papers

2022

End-To-End Neural Coreference Resolution Revisited: A Simple Yet Effective Baseline

ICASSP 2022accepted

Since the first end-to-end neural coreference resolution model was introduced, many extensions to the model have been proposed, ranging from using higher-order inference to directly optimizing evaluation metrics using reinforcement learning. Despite improving the coreference resolution performance b…

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2020

A Simple But Effective Bert Model for Dialog State Tracking on Resource-Limited Systems

Tuan Manh Lai, Quan Hung Tran, Trung Bui, Daisuke Kihara

ICASSP 2020accepted

In a task-oriented dialog system, the goal of dialog state tracking (DST) is to monitor the state of the conversation from the dialog history. Recently, many deep learning based methods have been proposed for the task. Despite their impressive performance, current neural architectures for DST are ty…

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