Seuraa
Johannes Welbl
Johannes Welbl
Research Scientist, Google DeepMind
Vahvistettu sähköpostiosoite verkkotunnuksessa google.com
Nimike
Viittaukset
Viittaukset
Vuosi
Complex embeddings for simple link prediction
T Trouillon, J Welbl, S Riedel, É Gaussier, G Bouchard
International conference on machine learning, 2071-2080, 2016
38872016
Training compute-optimal large language models
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
arXiv preprint arXiv:2203.15556, 2022
19362022
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
11532021
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
11332022
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
5872018
Crowdsourcing multiple choice science questions
J Welbl, NF Liu, M Gardner
arXiv preprint arXiv:1707.06209, 2017
4072017
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
3532017
Challenges in detoxifying language models
J Welbl, A Glaese, J Uesato, S Dathathri, J Mellor, LA Hendricks, ...
arXiv preprint arXiv:2109.07445, 2021
2492021
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
2142019
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
1852019
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
1822020
Frustratingly short attention spans in neural language modeling
M Daniluk, T Rocktäschel, J Welbl, S Riedel
arXiv preprint arXiv:1702.04521, 2017
1552017
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
1482022
Neural random forests
G Biau, E Scornet, J Welbl
Sankhya A 81 (2), 347-386, 2019
1432019
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
1232018
Cyprien de Masson d’Autume
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
1052021
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
702021
Making sense of sensory input
R Evans, J Hernández-Orallo, J Welbl, P Kohli, M Sergot
Artificial Intelligence 293, 103438, 2021
702021
Casting random forests as artificial neural networks (and profiting from it)
J Welbl
German Conference on Pattern Recognition, 765-771, 2014
512014
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
502022
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