Thuy-Trang Vu

Orcid: 0009-0005-6296-4184

According to our database1, Thuy-Trang Vu authored at least 22 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
PromptDSI: Prompt-based Rehearsal-free Instance-wise Incremental Learning for Document Retrieval.
CoRR, 2024

SCAR: Efficient Instruction-Tuning for Large Language Models via Style Consistency-Aware Response Ranking.
CoRR, 2024

Exploring the Potential of Multimodal LLM with Knowledge-Intensive Multimodal ASR.
CoRR, 2024

Mixture-of-Skills: Learning to Optimize Data Usage for Fine-Tuning Large Language Models.
CoRR, 2024

Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs.
CoRR, 2024

Conversational SimulMT: Efficient Simultaneous Translation with Large Language Models.
CoRR, 2024

Continual Learning for Large Language Models: A Survey.
CoRR, 2024

Adapting Large Language Models for Document-Level Machine Translation.
CoRR, 2024

Mixture-of-Skills: Learning to Optimize Data Usage for Fine-Tuning Large Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Exploring the Potential of Multimodal LLM with Knowledge-Intensive Multimodal ASR.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Simultaneous Machine Translation with Large Language Models.
CoRR, 2023

Active Continual Learning: Labelling Queries in a Sequence of Tasks.
CoRR, 2023

Koala: An Index for Quantifying Overlaps with Pre-training Corpora.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Systematic Assessment of Factual Knowledge in Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Learning to Adapt Neural Models with Limited Human Supervision in Natural Language Processing.
PhD thesis, 2022

Can Domains Be Transferred across Languages in Multi-Domain Multilingual Neural Machine Translation?
Proceedings of the Seventh Conference on Machine Translation, 2022

Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out Training.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
Effective Unsupervised Domain Adaptation with Adversarially Trained Language Models.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Learning How to Active Learn by Dreaming.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Automatic Post-Editing of Machine Translation: A Neural Programmer-Interpreter Approach.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018


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