Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better.

A. Kuncoro, C. Dyer, J. Hale, D. Yogatama, S. Clark, and P. Blunsom. ACL (1), page 1426-1436. Association for Computational Linguistics, (2018)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Phil Blunsom

Phil Zundel

Phil Langer

Phil Liebing

Phil Trinder

Other publications of authors with the same name

Hybrid computing using a neural network with dynamic external memoryA. Graves, G. Wayne, M. Reynolds, T. Harley, I. Danihelka, A. Grabska-Barwińska, S. Colmenarejo, E. Grefenstette, T. Ramalho, J. Agapiou and 10 other author(s). Nature, 538 (7626): 471--476 (October 2016)Counterfactual Data Augmentation for Neural Machine Translation.Q. Liu, M. Kusner, and P. Blunsom. NAACL-HLT, page 187-197. Association for Computational Linguistics, (2021)Learning with Stochastic Guidance for Navigation.L. Xie, Y. Miao, S. Wang, P. Blunsom, Z. Wang, C. Chen, A. Markham, and N. Trigoni. CoRR, (2018)LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better.A. Kuncoro, C. Dyer, J. Hale, D. Yogatama, S. Clark, and P. Blunsom. ACL (1), page 1426-1436. Association for Computational Linguistics, (2018)Relational Memory-Augmented Language Models.Q. Liu, D. Yogatama, and P. Blunsom. Trans. Assoc. Comput. Linguistics, (2022)Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions.S. Bhattamishra, A. Patel, P. Blunsom, and V. Kanade. ICLR, OpenReview.net, (2024)Human Feedback is not Gold Standard.T. Hosking, P. Blunsom, and M. Bartolo. ICLR, OpenReview.net, (2024)Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling.G. Melis, A. György, and P. Blunsom. J. Mach. Learn. Res., (2022)Hidden Markov ModelsP. Blunsom. (2004)Teaching Machines to Read and ComprehendK. Hermann, T. Kočiský, E. Grefenstette, L. Espeholt, W. Kay, M. Suleyman, and P. Blunsom. (2015)cite arxiv:1506.03340Comment: Appears in: Advances in Neural Information Processing Systems 28 (NIPS 2015). 14 pages, 13 figures.

BibSonomy

Disambiguation of "Blunsom, Phil"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better.

Please choose a person to relate this publication to

Phil Blunsom

Phil Zundel

Phil Langer

Phil Liebing

Phil Trinder

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Blunsom, Phil"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better.

Please choose a person to relate this publication to

Phil Blunsom

Phil Zundel

Phil Langer

Phil Liebing

Phil Trinder

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better.