Volgen
Sebastian Riedel
Sebastian Riedel
Honorary Professor @ University College London, Researcher @ DeepMind
Geverifieerd e-mailadres voor cs.ucl.ac.uk - Homepage
Titel
Geciteerd door
Geciteerd door
Jaar
Complex embeddings for simple link prediction
T Trouillon, J Welbl, S Riedel, É Gaussier, G Bouchard
International conference on machine learning, 2071-2080, 2016
28332016
Convolutional 2d knowledge graph embeddings
T Dettmers, P Minervini, P Stenetorp, S Riedel
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
23462018
Language models as knowledge bases?
F Petroni, T Rocktäschel, P Lewis, A Bakhtin, Y Wu, AH Miller, S Riedel
arXiv preprint arXiv:1909.01066, 2019
18382019
Modeling relations and their mentions without labeled text
S Riedel, L Yao, A McCallum
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
14362010
Retrieval-augmented generation for knowledge-intensive nlp tasks
P Lewis, E Perez, A Piktus, F Petroni, V Karpukhin, N Goyal, H Küttler, ...
Advances in Neural Information Processing Systems 33, 9459-9474, 2020
10962020
The CoNLL 2007 shared task on dependency parsing
J Nivre, J Hall, S Kübler, R McDonald, J Nilsson, S Riedel, D Yuret
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural …, 2007
8652007
Relation extraction with matrix factorization and universal schemas
S Riedel, L Yao, A McCallum, BM Marlin
Proceedings of the 2013 conference of the North American chapter of the …, 2013
7472013
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
4942018
Fact checking: Task definition and dataset construction
A Vlachos, S Riedel
Proceedings of the ACL 2014 workshop on language technologies and …, 2014
4562014
End-to-end differentiable proving
T Rocktäschel, S Riedel
Advances in neural information processing systems 30, 2017
4372017
Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
Y Lu, M Bartolo, A Moore, S Riedel, P Stenetorp
arXiv preprint arXiv:2104.08786, 2021
4092021
TaBERT: Pretraining for joint understanding of textual and tabular data
P Yin, G Neubig, W Yih, S Riedel
arXiv preprint arXiv:2005.08314, 2020
3902020
Scalable zero-shot entity linking with dense entity retrieval
L Wu, F Petroni, M Josifoski, S Riedel, L Zettlemoyer
arXiv preprint arXiv:1911.03814, 2019
3762019
Semeval 2017 task 10: Scienceie-extracting keyphrases and relations from scientific publications
I Augenstein, M Das, S Riedel, L Vikraman, A McCallum
arXiv preprint arXiv:1704.02853, 2017
3752017
MLQA: Evaluating cross-lingual extractive question answering
P Lewis, B Oğuz, R Rinott, S Riedel, H Schwenk
arXiv preprint arXiv:1910.07475, 2019
3562019
emoji2vec: Learning emoji representations from their description
B Eisner, T Rocktäschel, I Augenstein, M Bošnjak, S Riedel
arXiv preprint arXiv:1609.08359, 2016
3212016
KILT: a benchmark for knowledge intensive language tasks
F Petroni, A Piktus, A Fan, P Lewis, M Yazdani, N De Cao, J Thorne, ...
arXiv preprint arXiv:2009.02252, 2020
3102020
Autoregressive entity retrieval
N De Cao, G Izacard, S Riedel, F Petroni
arXiv preprint arXiv:2010.00904, 2020
3002020
Injecting logical background knowledge into embeddings for relation extraction
T Rocktäschel, S Singh, S Riedel
Proceedings of the 2015 conference of the north American Chapter of the …, 2015
2892015
Knowledge graph completion via complex tensor factorization
T Trouillon, CR Dance, J Welbl, S Riedel, É Gaussier, G Bouchard
arXiv preprint arXiv:1702.06879, 2017
2852017
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–20