Projects per year
Personal profile
Biography
Trang Vu is a Lecturer in Department of Data Science and Artificial Intelligence, Faculty of Information Technology, Monash University. Her research interests lie at the intersection of natural language processing and machine learning. Her current research focuses on efficient and trustworthy NLP methods to make NLP technologies safe and accessible.
My current research interests include
- Safe and trustworthy NLP: alignment and hallucination mitigation for LLMs
- Cultural-aware machine translation
- ML methods to facilitate efficient NLP such as active learning, transfer learning and semi-supervised learning
Education/Academic qualification
AI and Machine Learning, Doctoral of Philosophy, Learning to Adapt Neural Models with Limited Human Supervision in Natural Language Processing, Department of Data Science & AI
Award Date: 26 Oct 2022
Collaborations and top research areas from the last five years
Projects
- 2 Active
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TMLGenAI: Trustworthy Generative AI: Towards Safe and Aligned Foundation Models
Phung, D., Vu, T., Shareghi Nojehdeh, E., Qu, L., Le, T., Haffari, R., Webb, G. & Nicholson, A.
11/06/24 → 10/07/26
Project: Research
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Aligning Large Language Models with Human Intention: Aligning Large Language Models with Human Intention
4/07/23 → 21/12/26
Project: Research
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Automatic evaluation of shared decision making in maternity care with natural language processing
Waddell, A., Vu, T., Pollock, W. E., Lokmic-Tomkins, Z., Watkins, V., Valentine, K. D. & Olivier, P. L., Jul 2024, In: BMJ Evidence-Based Medicine. 29, S1, p. A136 1 p., 287.Research output: Contribution to journal › Meeting Abstract › peer-review
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Exploring the Potential of Multimodal LLM with Knowledge-Intensive Multimodal ASR
Wang, M., Wang, Y., Vu, T-T., Shareghi, E. & Haffari, R., 2024, EMNLP 2024, The 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024. Al-Onaizan, Y., Bansal, M. & Chen, Y-N. (eds.). Kerrville TX USA: Association for Computational Linguistics (ACL), p. 13274–13288 15 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access -
Koala: An index for quantifying overlaps with pre-training corpora
Vu, T., He, X., Haffari, R. & Shareghi, E., 2023, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Feng, Y. & Lefever, E. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 90-98 9 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access -
Can domains be transferred across languages in multi-domain multilingual Neural Machine Translation?
Vu, T. T., Khadivi, S., He, X., Phung, D. & Haffari, G., 2022, WMT 2022 - Seventh Conference on Machine Translation - Proceedings of the Conference. Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 381-396 16 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile1 Citation (Scopus) -
Domain generalisation of NMT: fusing adapters with leave-one-domain-out training
Vu, T-T., Khadivi, S., Phung, D. & Haffari, G., 2022, ACL 2022 - The 60th Annual Meeting of the Association for Computational Linguistics - Findings of ACL 2022. Muresan, S., Nakov, P. & Villavicencio, A. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 582-588 7 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile7 Citations (Scopus)