| Recurrent neural network grammars C Dyer, A Kuncoro, M Ballesteros, NA Smith arXiv preprint arXiv:1602.07776, 2016 | 425 | 2016 |
| Dynet: The dynamic neural network toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint, 2017 | 357* | 2017 |
| What do recurrent neural network grammars learn about syntax? A Kuncoro, M Ballesteros, L Kong, C Dyer, G Neubig, NA Smith Proceedings of EACL 2017 1, 1249-1258, 2017 | 112 | 2017 |
| LSTMs can learn syntax-sensitive dependencies well, but modeling structure makes them better A Kuncoro, C Dyer, J Hale, D Yogatama, S Clark, P Blunsom Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 96 | 2018 |
| Distilling an ensemble of greedy dependency parsers into one MST parser A Kuncoro, M Ballesteros, L Kong, C Dyer, NA Smith Proceedings of EMNLP, 1744-1753, 2016 | 69 | 2016 |
| Finding syntax in human encephalography with beam search J Hale, C Dyer, A Kuncoro, JR Brennan arXiv preprint arXiv:1806.04127, 2018 | 65 | 2018 |
| Unsupervised recurrent neural network grammars Y Kim, AM Rush, L Yu, A Kuncoro, C Dyer, G Melis arXiv preprint arXiv:1904.03746, 2019 | 63 | 2019 |
| Memory architectures in recurrent neural network language models D Yogatama, Y Miao, G Melis, W Ling, A Kuncoro, C Dyer, P Blunsom International Conference on Learning Representations, 2018 | 41 | 2018 |
| Implicit causal models for genome-wide association studies D Tran, DM Blei arXiv preprint arXiv:1710.10742, 2017 | 30 | 2017 |
| Scalable Syntax-Aware Language Models Using Knowledge Distillation A Kuncoro, C Dyer, L Rimell, S Clark, P Blunsom arXiv preprint arXiv:1906.06438, 2019 | 17 | 2019 |
| Localizing syntactic predictions using recurrent neural network grammars JR Brennan, C Dyer, A Kuncoro, JT Hale Neuropsychologia 146, 107479, 2020 | 5 | 2020 |
| The perils of natural behaviour tests for unnatural models: the case of number agreement A Kuncoro, C Dyer, J Hale, P Blunsom Poster presented at Learning Language in Humans and in Machines, Paris, Fr …, 2018 | 4 | 2018 |
| Syntactic Structure Distillation Pretraining for Bidirectional Encoders A Kuncoro, L Kong, D Fried, D Yogatama, L Rimell, C Dyer, P Blunsom Transactions of the Association for Computational Linguistics 8, 776-794, 2020 | 3 | 2020 |
| Text genre and training data size in human-like parsing J Hale, A Kuncoro, K Hall, C Dyer, J Brennan Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 2 | 2019 |
| Dependency parsing with lstms: An empirical evaluation A Kuncoro, Y Sawai, K Duh, Y Matsumoto arXiv preprint arXiv:1604.06529, 2016 | 2 | 2016 |
| IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation S Cahyawijaya, GI Winata, B Wilie, K Vincentio, X Li, A Kuncoro, S Ruder, ... arXiv preprint arXiv:2104.08200, 2021 | | 2021 |
| Pitfalls of Static Language Modelling A Lazaridou, A Kuncoro, E Gribovskaya, D Agrawal, A Liska, T Terzi, ... arXiv preprint arXiv:2102.01951, 2021 | | 2021 |
| Cross-lingual Log Bi-linear Dependency Parsing A Kuncoro University of Oxford, 2014 | | 2014 |
| Syntactic Structure Distillation Pretraining for Bidirectional Encoders Download PDF A Kuncoro | | |
Chris DyerDeepMind, Carnegie MellonVerified email at google.com
