Papers by Doan Nam Long Vu

2 papers
DP-NMT: Scalable Differentially Private Machine Translation (2024.eacl-demo)

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Challenge: Neural machine translation (NMT) is a popular text generation task, yet there is nagging data privacy concerns.
Approach: They propose an open-source framework for a privacy-preserving NMT with DP-SGD.
Outcome: The proposed framework is open-source and open to the public . it combines models, datasets, and evaluation metrics to demonstrate its effectiveness.
Layer or Representation Space: What Makes BERT-based Evaluation Metrics Robust? (2022.coling-1)

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Challenge: Recent embedding-based evaluation metrics for text generation are based on measuring correlation with human evaluations on standard benchmarks.
Approach: They examine the robustness of BERTScore, one of the most popular embedding-based metrics for text generation.
Outcome: The embedding-based metrics that have the highest correlation with human evaluations on a standard benchmark can have the lowest correlation if the amount of input noise or unknown tokens increases.

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