Papers by Nham Le
AutoNLU: An On-demand Cloud-based Natural Language Understanding System for Enterprises (2020.aacl-demo)
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| Challenge: | AutoNLU is an on-demand cloud-based system that enables users to create and edit datasets and train and test different state-of-the-art NLU models. |
| Approach: | They introduce an on-demand cloud-based system that provides an easy-to-use interface . they build powerful keyphrase extraction models that achieve state-of-the-art results . |
| Outcome: | The proposed model achieves state-of-the-art on two public benchmarks and is easy to use and use. |
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 . |