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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
33402016
Training compute-optimal large language models
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
arXiv preprint arXiv:2203.15556, 2022
11702022
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
8462021
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
7502022
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
5342018
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
3192017
Crowdsourcing multiple choice science questions
J Welbl, NF Liu, M Gardner
arXiv preprint arXiv:1707.06209, 2017
2542017
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
1782019
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
1762019
Challenges in detoxifying language models
J Welbl, A Glaese, J Uesato, S Dathathri, J Mellor, LA Hendricks, ...
arXiv preprint arXiv:2109.07445, 2021
1722021
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
1592020
Frustratingly short attention spans in neural language modeling
M Daniluk, T Rocktäschel, J Welbl, S Riedel
arXiv preprint arXiv:1702.04521, 2017
1462017
Neural random forests
G Biau, E Scornet, J Welbl
Sankhya A 81 (2), 347-386, 2019
1332019
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
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
1052022
Cyprien de Masson d’Autume
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
892021
Making sense of sensory input
R Evans, J Hernández-Orallo, J Welbl, P Kohli, M Sergot
Artificial Intelligence 293, 103438, 2021
632021
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
562021
Casting random forests as artificial neural networks (and profiting from it)
J Welbl
German Conference on Pattern Recognition, 765-771, 2014
482014
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
362022
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