Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 888 | 2023 |
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 | 141 | 2024 |
Slic-hf: Sequence likelihood calibration with human feedback Y Zhao, R Joshi, T Liu, M Khalman, M Saleh, PJ Liu arXiv preprint arXiv:2305.10425, 2023 | 119 | 2023 |
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 | 91 | 2023 |
Calibrating sequence likelihood improves conditional language generation Y Zhao, M Khalman, R Joshi, S Narayan, M Saleh, PJ Liu The eleventh international conference on learning representations, 2022 | 83 | 2022 |
Statistical rejection sampling improves preference optimization T Liu, Y Zhao, R Joshi, M Khalman, M Saleh, PJ Liu, J Liu arXiv preprint arXiv:2309.06657, 2023 | 72 | 2023 |
Direct language model alignment from online ai feedback S Guo, B Zhang, T Liu, T Liu, M Khalman, F Llinares, A Rame, T Mesnard, ... arXiv preprint arXiv:2402.04792, 2024 | 31 | 2024 |
ForumSum: A multi-speaker conversation summarization dataset M Khalman, Y Zhao, M Saleh Findings of the Association for Computational Linguistics: EMNLP 2021, 4592-4599, 2021 | 20 | 2021 |
Lipo: Listwise preference optimization through learning-to-rank T Liu, Z Qin, J Wu, J Shen, M Khalman, R Joshi, Y Zhao, M Saleh, ... arXiv preprint arXiv:2402.01878, 2024 | 12 | 2024 |
Calibrating Likelihoods towards Consistency in Summarization Models P Zablotskaia, M Khalman, R Joshi, LB Soares, S Jakobovits, J Maynez, ... arXiv preprint arXiv:2310.08764, 2023 | 1 | 2023 |