Papers by Nhan Dam

2 papers
Scene Graph Modification Based on Natural Language Commands (2020.findings-emnlp)

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Challenge: Numerous parsing methods have been developed for a single sentence, while a typical human-computer interaction session or conversation is not singleturn.
Approach: They propose to modify an existing scene graph given a new user's command by using graph-based sparse transformer and cross attention information fusion to improve performance.
Outcome: The proposed models outperform previous systems adapted from the machine translation and graph generation literature and contribute to the research community.
Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering (2020.coling-main)

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Challenge: Interpretability and explainability of deep neural net models are always challenging due to their size and complexity.
Approach: They propose to design an explainable, evidence-based memory network architecture that connects current sample with seen samples and bases its decision on these samples.
Outcome: The proposed model can trace errors to training instances that might have caused errors . the proposed model achieves state-of-the-art performance on two popular datasets .

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