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Johannes Welbl
Johannes Welbl
Research Scientist, Google DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
Complex embeddings for simple link prediction
T Trouillon, J Welbl, S Riedel, É Gaussier, G Bouchard
International conference on machine learning, 2071-2080, 2016
32702016
Training compute-optimal large language models
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
arXiv preprint arXiv:2203.15556, 2022
10382022
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
8052021
Competition-level code generation with alphacode
Y Li, D Choi, J Chung, N Kushman, J Schrittwieser, R Leblond, T Eccles, ...
Science 378 (6624), 1092-1097, 2022
6982022
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
5292018
Knowledge graph completion via complex tensor factorization
T Trouillon, CR Dance, É Gaussier, J Welbl, S Riedel, G Bouchard
Journal of Machine Learning Research 18 (130), 1-38, 2017
3142017
Crowdsourcing multiple choice science questions
J Welbl, NF Liu, M Gardner
arXiv preprint arXiv:1707.06209, 2017
2312017
Achieving verified robustness to symbol substitutions via interval bound propagation
PS Huang, R Stanforth, J Welbl, C Dyer, D Yogatama, S Gowal, ...
arXiv preprint arXiv:1909.01492, 2019
1752019
Reducing sentiment bias in language models via counterfactual evaluation
PS Huang, H Zhang, R Jiang, R Stanforth, J Welbl, J Rae, V Maini, ...
arXiv preprint arXiv:1911.03064, 2019
1702019
Challenges in detoxifying language models
J Welbl, A Glaese, J Uesato, S Dathathri, J Mellor, LA Hendricks, ...
arXiv preprint arXiv:2109.07445, 2021
1572021
Beat the AI: Investigating adversarial human annotation for reading comprehension
M Bartolo, A Roberts, J Welbl, S Riedel, P Stenetorp
Transactions of the Association for Computational Linguistics 8, 662-678, 2020
1512020
Frustratingly short attention spans in neural language modeling
M Daniluk, T Rocktäschel, J Welbl, S Riedel
arXiv preprint arXiv:1702.04521, 2017
1452017
Neural random forests
G Biau, E Scornet, J Welbl
Sankhya A 81 (2), 347-386, 2019
1312019
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
1182018
Cyprien de Masson d’Autume
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
842021
An empirical analysis of compute-optimal large language model training
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
Advances in Neural Information Processing Systems 35, 30016-30030, 2022
802022
Making sense of sensory input
R Evans, J Hernández-Orallo, J Welbl, P Kohli, M Sergot
Artificial Intelligence 293, 103438, 2021
612021
Cyprien de Masson d’Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, HF Song, J Aslanides, ...
Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William S. Isaac …, 2021
502021
Casting random forests as artificial neural networks (and profiting from it)
J Welbl
German Conference on Pattern Recognition, 765-771, 2014
492014
Characteristics of harmful text: Towards rigorous benchmarking of language models
M Rauh, J Mellor, J Uesato, PS Huang, J Welbl, L Weidinger, S Dathathri, ...
Advances in Neural Information Processing Systems 35, 24720-24739, 2022
302022
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