| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... Technical report: https://arxiv.org/pdf/2312.11805, 2023 | 601 | 2023 |
| The Flan Collection: Designing Data and Methods for Effective Instruction Tuning S Longpre, L Hou, T Vu, A Webson, HW Chung, Y Tay, D Zhou, QV Le, ... ICML, 2023 | 362 | 2023 |
| SPoT: Better frozen model adaptation through soft prompt transfer T Vu, B Lester, N Constant, R Al-Rfou, D Cer ACL, 2022 | 210 | 2022 |
| Exploring and Predicting Transferability across NLP Tasks T Vu, T Wang, T Munkhdalai, A Sordoni, A Trischler, A Mattarella-Micke, ... EMNLP, 2020 | 133 | 2020 |
| JAIST: Combining multiple features for answer selection in community question answering Q Tran, V Tran, T Vu, M Nguyen, S Pham SemEval@NAACL, 2015 | 96 | 2015 |
| Sentence Simplification with Memory-Augmented Neural Networks T Vu, B Hu, T Munkhdalai, H Yu NAACL, 2018 | 81 | 2018 |
| STraTA: Self-Training with Task Augmentation for Better Few-shot Learning T Vu, MT Luong, QV Le, G Simon, M Iyyer EMNLP, 2021 | 47 | 2021 |
| FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation T Vu, M Iyyer, X Wang, N Constant, J Wei, J Wei, C Tar, YH Sung, D Zhou, ... ACL Findings, 2024 | 46 | 2024 |
| Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation T Vu, A Barua, B Lester, D Cer, M Iyyer, N Constant EMNLP, 2022 | 41 | 2022 |
| Mixture-of-experts meets instruction tuning: A winning combination for large language models S Shen, L Hou, Y Zhou, N Du, S Longpre, J Wei, HW Chung, B Zoph, ... ICLR, 2024 | 25 | 2024 |
| Learning to simplify children stories with limited data T Vu, G Tran, S Pham ACIIDS, 2014 | 22 | 2014 |
| Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts S Shen, L Hou, Y Zhou, N Du, S Longpre, J Wei, HW Chung, B Zoph, ... ICLR, 2024 | 19 | 2024 |
| Integrating Multiplicative Features into Supervised Distributional Methods for Lexical Entailment T Vu, V Shwartz *SEM@NAACL, 2018 | 16 | 2018 |
| Dialect-robust Evaluation of Generated Text J Sun, T Sellam, E Clark, T Vu, T Dozat, D Garrette, A Siddhant, ... ACL, 2023 | 11 | 2023 |
| Leveraging QA Datasets to Improve Generative Data Augmentation D Mekala, T Vu, T Schick, J Shang EMNLP, 2022 | 10 | 2022 |
| Self-Evaluation Improves Selective Generation in Large Language Models J Ren, Y Zhao, T Vu, PJ Liu, B Lakshminarayanan ICBINB@NeurIPS, 2023 | 7 | 2023 |
| Encouraging Paragraph Embeddings to Remember Sentence Identity Improves Classification T Vu, M Iyyer ACL, 2019 | 4 | 2019 |
| TATO: Leveraging on Multiple Strategies for Semantic Textual Similarity T Vu, Q Tran, S Pham SemEval@NAACL, 2015 | 2 | 2015 |
| Frozen Model Adaptation Through Soft Prompt Transfer TT Vu, DM Cer, N Constant, BD Lester, R Al-rfou US Patent App. 17/863,840, 2024 | | 2024 |
| Effective and Efficient Transfer Learning in the Era of Large Language Models T Vu Doctoral Dissertation, University of Massachusetts Amherst, 2023 | | 2023 |
Denny ZhouResearch Scientist, Google DeepMindVerified email at google.com
