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 | 753 | 2021 |
Mind the Gap: Assessing Temporal Generalization in Neural Language Models A Lazaridou, A Kuncoro, E Gribovskaya, D Agrawal, A Liska, T Terzi, ... arXiv preprint arXiv:2102.01951, 2021 | 184* | 2021 |
Streamingqa: A benchmark for adaptation to new knowledge over time in question answering models A Liska, T Kocisky, E Gribovskaya, T Terzi, E Sezener, D Agrawal, ... International Conference on Machine Learning, 13604-13622, 2022 | 21 | 2022 |
Scaling Language Models: Methods JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, HF Song, J Aslanides, ... Analysis & Insights from Training Gopher. arXiv, 2021 | 18 | 2021 |
Cyprien de Masson d’Autume, Tim Scholtes, Manzil Zaheer, Susannah Young, Ellen Gilsenan-McMahon, Sophia Austin, Phil Blunsom, and Angeliki Lazaridou. 2022. Streamingqa: A … A Liska, T Kociský, E Gribovskaya, T Terzi, E Sezener, D Agrawal International Conference on Machine Learning, 2022 | 8 | 2022 |
Detecting semi-plausible response patterns T Terzi London School of Economics and Political Science, 2017 | 5 | 2017 |
Scaling Instructable Agents Across Many Simulated Worlds S Team, M Abi Raad, A Ahuja, C Barros, F Besse, A Bolt, A Bolton, ... | | 2024 |