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Doan Nam Long Vu
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2020 – today
- 2024
- [c3]Timour Igamberdiev, Doan Nam Long Vu, Felix Künnecke, Zhuo Yu, Jannik Holmer, Ivan Habernal:
DP-NMT: Scalable Differentially Private Machine Translation. EACL (Demonstrations) 2024: 94-105 - [c2]Doan Nam Long Vu, Timour Igamberdiev, Ivan Habernal:
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translation. EMNLP (Findings) 2024: 507-527 - [i4]Doan Nam Long Vu, Timour Igamberdiev, Ivan Habernal:
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translation. CoRR abs/2407.18789 (2024) - [i3]Yufang Hou, Thy Thy Tran, Doan Nam Long Vu, Yiwen Cao, Kai Li, Lukas Rohde, Iryna Gurevych:
A Course Shared Task on Evaluating LLM Output for Clinical Questions. CoRR abs/2408.00122 (2024) - 2023
- [i2]Timour Igamberdiev, Doan Nam Long Vu, Felix Künnecke, Zhuo Yu, Jannik Holmer, Ivan Habernal:
DP-NMT: Scalable Differentially-Private Machine Translation. CoRR abs/2311.14465 (2023) - 2022
- [c1]Doan Nam Long Vu, Nafise Sadat Moosavi, Steffen Eger:
Layer or Representation Space: What Makes BERT-based Evaluation Metrics Robust? COLING 2022: 3401-3411 - [i1]Doan Nam Long Vu, Nafise Sadat Moosavi, Steffen Eger:
Layer or Representation Space: What makes BERT-based Evaluation Metrics Robust? CoRR abs/2209.02317 (2022)
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