| Meta Networks T Munkhdalai, H Yu ICML 2017, 2017 | 1406 | 2017 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 997 | 2024 |
| The CHEMDNER corpus of chemicals and drugs and its annotation principles M Krallinger, O Rabal, F Leitner, M Vazquez, D Salgado, Z Lu, R Leaman, ... Journal of cheminformatics 7, 1-17, 2015 | 380 | 2015 |
| Rapid adaptation with conditionally shifted neurons T Munkhdalai, X Yuan, S Mehri, A Trischler ICML 2018, 3661-3670, 2018 | 356 | 2018 |
| Neural Semantic Encoders T Munkhdalai, H Yu EACL 2017, 2016 | 189* | 2016 |
| Exploring and predicting transferability across NLP tasks T Vu, T Wang, T Munkhdalai, A Sordoni, A Trischler, A Mattarella-Micke, ... arXiv preprint arXiv:2005.00770, 2020 | 175 | 2020 |
| An empirical comparison of machine-learning methods on bank client credit assessments L Munkhdalai, T Munkhdalai, OE Namsrai, JY Lee, KH Ryu Sustainability 11 (3), 699, 2019 | 174 | 2019 |
| Neural tree indexers for text understanding T Munkhdalai, H Yu EACL 2017 1, 11, 2017 | 116 | 2017 |
| Mixture of activation functions with extended min-max normalization for forex market prediction L Munkhdalai, T Munkhdalai, KH Park, HG Lee, M Li, KH Ryu IEEE Access 7, 183680-183691, 2019 | 104 | 2019 |
| Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention T Munkhdalai, M Faruqui, S Gopal arXiv preprint arXiv:2404.07143, 2024 | 92 | 2024 |
| Self-supervised meta-learning for few-shot natural language classification tasks T Bansal, R Jha, T Munkhdalai, A McCallum arXiv preprint arXiv:2009.08445, 2020 | 91 | 2020 |
| Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension R Das, T Munkhdalai, X Yuan, A Trischler, A McCallum ICLR 2019, 2018 | 91 | 2018 |
| Clinical relation extraction toward drug safety surveillance using electronic health record narratives: classical learning versus deep learning T Munkhdalai, F Liu, H Yu JMIR public health and surveillance 4 (2), e9361, 2018 | 87 | 2018 |
| Sentence Simplification with Memory-Augmented Neural Networks T Vu, B Hu, T Munkhdalai, H Yu NAACL 2018, 2018 | 87 | 2018 |
| Metalearned Neural Memory T Munkhdalai, A Sordoni, T Wang, A Trischler NeurIPS 2019, 2019 | 72 | 2019 |
| An end-to-end adaptive input selection with dynamic weights for forecasting multivariate time series L Munkhdalai, T Munkhdalai, KH Park, T Amarbayasgalan, E Batbaatar, ... IEEE Access 7, 99099-99114, 2019 | 69 | 2019 |
| Incorporating domain knowledge in chemical and biomedical named entity recognition with word representations T Munkhdalai, M Li, K Batsuren, HA Park, NH Choi, KH Ryu Journal of cheminformatics 7, 1-8, 2015 | 65 | 2015 |
| Diverse distributions of self-supervised tasks for meta-learning in NLP T Bansal, K Gunasekaran, T Wang, T Munkhdalai, A McCallum arXiv preprint arXiv:2111.01322, 2021 | 57 | 2021 |
| A feature selection-based ensemble method for arrhythmia classification E Namsrai, T Munkhdalai, M Li, JH Shin, OE Namsrai, KH Ryu Journal of Information Processing Systems 9 (1), 31-40, 2013 | 52 | 2013 |
| Learning associative inference using fast weight memory I Schlag, T Munkhdalai, J Schmidhuber arXiv preprint arXiv:2011.07831, 2020 | 50 | 2020 |
Keun Ho RyuChungbuk National UniversityEmail verificata su chungbuk.ac.kr