Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 2513 | 2023 |
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 | 1148 | 2021 |
Ethical and social risks of harm from language models L Weidinger, J Mellor, M Rauh, C Griffin, J Uesato, PS Huang, M Cheng, ... arXiv preprint arXiv:2112.04359, 2021 | 1001 | 2021 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 960 | 2024 |
Taxonomy of risks posed by language models L Weidinger, J Uesato, M Rauh, C Griffin, PS Huang, J Mellor, A Glaese, ... Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 618 | 2022 |
Red teaming language models with language models E Perez, S Huang, F Song, T Cai, R Ring, J Aslanides, A Glaese, ... arXiv preprint arXiv:2202.03286, 2022 | 597 | 2022 |
Improving alignment of dialogue agents via targeted human judgements A Glaese, N McAleese, M Trębacz, J Aslanides, V Firoiu, T Ewalds, ... arXiv preprint arXiv:2209.14375, 2022 | 469 | 2022 |
Gemini: A family of highly capable multimodal models R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805 1, 2023 | 307 | 2023 |
Challenges in detoxifying language models J Welbl, A Glaese, J Uesato, S Dathathri, J Mellor, LA Hendricks, ... arXiv preprint arXiv:2109.07445, 2021 | 238 | 2021 |
Fine-tuning language models to find agreement among humans with diverse preferences M Bakker, M Chadwick, H Sheahan, M Tessler, L Campbell-Gillingham, ... Advances in Neural Information Processing Systems 35, 38176-38189, 2022 | 222 | 2022 |
Teaching language models to support answers with verified quotes J Menick, M Trebacz, V Mikulik, J Aslanides, F Song, M Chadwick, ... arXiv preprint arXiv:2203.11147, 2022 | 215 | 2022 |
Cyprien de Masson d’Autume JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ... | 106 | 2021 |
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 | 70 | 2021 |
Androidenv: A reinforcement learning platform for android D Toyama, P Hamel, A Gergely, G Comanici, A Glaese, Z Ahmed, ... arXiv preprint arXiv:2105.13231, 2021 | 65 | 2021 |
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 | 49 | 2022 |
OpenAI o1 System Card A Jaech, A Kalai, A Lerer, A Richardson, A El-Kishky, A Low, A Helyar, ... arXiv preprint arXiv:2412.16720, 2024 | 29 | 2024 |
Red Teaming Language Models with Language Models, February 2022a E Perez, S Huang, F Song, T Cai, R Ring, J Aslanides, A Glaese, ... URL https://arxiv. org/abs/2202.03286 v1, 0 | 25 | |
Enabling flexible automation system hardware: Dynamic reconfiguration of a real-time capable field-bus D Regulin, A Glaese, S Feldmann, D Schütz, B Vogel-Heuser 2015 IEEE 13th International Conference on Industrial Informatics (INDIN …, 2015 | 13 | 2015 |
Measuring short-form factuality in large language models J Wei, N Karina, HW Chung, YJ Jiao, S Papay, A Glaese, J Schulman, ... arXiv preprint arXiv:2411.04368, 2024 | 12 | 2024 |
Teaching language models to support answers with verified quotes, 2022 J Menick, M Trebacz, V Mikulik, J Aslanides, F Song, M Chadwick, ... URL https://arxiv. org/abs/2203.11147, 2022 | 11 | 2022 |