Pontus Stenetorp
Pontus Stenetorp
Lecturer, University College London
Verified email at is.s.u-tokyo.ac.jp - Homepage
Cited by
Cited by
BRAT: a Web-based Tool for NLP-Assisted Text Annotation
P Stenetorp, S Pyysalo, G Topić, T Ohta, S Ananiadou, J Tsujii
13th Conference of the European Chapter of the Association for Computational …, 2012
Convolutional 2D Knowledge Graph Embeddings
T Dettmers, P Minervini, P Stenetorp, S Riedel
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Constructing datasets for multi-hop reading comprehension across documents
J Welbl, P Stenetorp, S Riedel
Transactions of the Association for Computational Linguistics 6, 287-302, 2018
Neural Architectures for Fine-grained Entity Type Classification
S Shimaoka, P Stenetorp, K Inui, S Riedel
arXiv preprint arXiv:1606.01341, 2016
An Attentive Neural Architecture for Fine-grained Entity Type Classification
S Shimaoka, P Stenetorp, K Inui, S Riedel
arXiv preprint arXiv:1604.05525, 2016
Task-Oriented Learning of Word Embeddings for Semantic Relation Classification
K Hashimoto, P Stenetorp, M Miwa, Y Tsuruoka
arXiv preprint arXiv:1503.00095, 2015
BioNLP Shared Task 2011: Supporting Resources
P Stenetorp, T Goran, P Sampo, O Tomoko, K Jin-Dong, J Tsujii
BioNLP 2011 Workshop, 112–120, 2011
BioNLP shared task 2013: supporting resources
P Stenetorp, W Golik, T Hamon, DC Comeau, RI Dogan, H Liu, WJ Wilbur
Proceedings of the BioNLP Shared Task 2013 Workshop. Association for …, 2013
UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)
T Yoneda, J Mitchell, J Welbl, P Stenetorp, S Riedel
Proceedings of the First Workshop on Fact Extraction and VERification (FEVER …, 2018
Transition-based Dependency Parsing Using Recursive Neural Networks
P Stenetorp
Deep Learning Workshop at NIPS 2013, 2013
Jointly Learning Word Representations and Composition Functions Using Predicate-Argument Structures
K Hashimoto, P Stenetorp, M Miwa, Y Tsuruoka
Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014
Leveraging Monolingual Data for Crosslingual Compositional Word Representations
H Soyer, P Stenetorp, A Aizawa
arXiv preprint arXiv:1412.6334, 2014
Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection
S Kasewa, P Stenetorp, S Riedel
arXiv preprint arXiv:1810.00668, 2018
Size (and Domain) Matters: Evaluating Semantic Word Space Representations for Biomedical Text
P Stenetorp, H Soyer, S Pyysalo, S Ananiadou, T Chikayama
5th International Symposium on Semantic Mining in Biomedicine, 42-49, 2012
On the Importance of Strong Baselines in Bayesian Deep Learning
J Mukhoti, P Stenetorp, Y Gal
arXiv preprint arXiv:1811.09385, 2018
Assessing the benchmarking capacity of machine reading comprehension datasets
S Sugawara, P Stenetorp, K Inui, A Aizawa
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8918-8927, 2020
Automated Extraction of Swedish Neologisms Using a Temporally Annotated Corpus
P Stenetorp
Royal Institute of Technology (KTH), 2010
Extrapolation in NLP
J Mitchell, P Minervini, P Stenetorp, S Riedel
arXiv preprint arXiv:1805.06648, 2018
Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets
P Lewis, P Stenetorp, S Riedel
arXiv preprint arXiv:2008.02637, 2020
Sharing annotations better: RESTful Open Annotation
S Pyysalo, J Campos, JM Cejuela, F Ginter, K Hakala, C Li, P Stenetorp, ...
ACL-IJCNLP 2015, 91, 2015
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