Adhiguna Kuncoro
Adhiguna Kuncoro
Oxford University and Google DeepMind
Verified email at - Homepage
Cited by
Cited by
Localizing syntactic predictions using recurrent neural network grammars
JR Brennan, C Dyer, A Kuncoro, JT Hale
Neuropsychologia 146, 107479, 2020
Dynet: The dynamic neural network toolkit
G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ...
arXiv preprint, 2017
Scaling language models: Methods, analysis & insights from training gopher
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
arXiv preprint arXiv:2112.11446, 2021
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
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
Unsupervised recurrent neural network grammars
Y Kim, AM Rush, L Yu, A Kuncoro, C Dyer, G Melis
arXiv preprint arXiv:1904.03746, 2019
Finding syntax in human encephalography with beam search
J Hale, C Dyer, A Kuncoro, JR Brennan
arXiv preprint arXiv:1806.04127, 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
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
Mind the gap: Assessing temporal generalization in neural language models
A Lazaridou, A Kuncoro, E Gribovskaya, D Agrawal, A Liska, T Terzi, ...
Advances in Neural Information Processing Systems 34, 29348-29363, 2021
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
Cyprien de Masson d’Autume
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
Scalable syntax-aware language models using knowledge distillation
A Kuncoro, C Dyer, L Rimell, S Clark, P Blunsom
arXiv preprint arXiv:1906.06438, 2019
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
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
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
Transformer Grammars: Augmenting Transformer language models with syntactic inductive biases at scale
L Sartran, S Barrett, A Kuncoro, M Stanojević, P Blunsom, C Dyer
Transactions of the Association for Computational Linguistics 10, 1423-1439, 2022
Do Language Models Learn Commonsense Knowledge?
XL Li, A Kuncoro, CM d'Autume, P Blunsom, A Nematzadeh
arXiv preprint arXiv:2111.00607, 2021
Dependency parsing with lstms: An empirical evaluation
A Kuncoro, Y Sawai, K Duh, Y Matsumoto
arXiv preprint arXiv:1604.06529, 2016
A systematic investigation of commonsense knowledge in large language models
XL Li, A Kuncoro, J Hoffmann, C de Masson d’Autume, P Blunsom, ...
Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022
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