| 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 | 3311 | 2023 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 1199 | 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 | 248 | 2023 |
| Large language models are effective text rankers with pairwise ranking prompting Z Qin, R Jagerman, K Hui, H Zhuang, J Wu, J Shen, T Liu, J Liu, D Metzler, ... 2024 Annual Conference of the North American Chapter of the Association for …, 2024 | 209 | 2024 |
| Statistical rejection sampling improves preference optimization T Liu, Y Zhao, R Joshi, M Khalman, M Saleh, PJ Liu, J Liu ICLR 2024, 2024 | 173 | 2024 |
| 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 | 108 | 2024 |
| Characterizing spatiotemporal transcriptome of the human brain via low-rank tensor decomposition T Liu, M Yuan, H Zhao Statistics in Biosciences 14 (3), 485-513, 2022 | 53 | 2022 |
| A deep probabilistic model for customer lifetime value prediction X Wang, T Liu, J Miao arXiv preprint arXiv:1912.07753, 2019 | 42 | 2019 |
| Lipo: Listwise preference optimization through learning-to-rank T Liu, Z Qin, J Wu, J Shen, M Khalman, R Joshi, Y Zhao, M Saleh, ... NAACL 2025, 2025 | 32 | 2025 |
| Human alignment of large language models through online preference optimisation D Calandriello, D Guo, R Munos, M Rowland, Y Tang, BA Pires, ... ICML 2024, 2024 | 32 | 2024 |
| NewsEmbed: modeling news through pre-trained document representations J Liu, T Liu, C Yu Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 17 | 2021 |
| Building Math Agents with Multi-Turn Iterative Preference Learning W Xiong, C Shi, J Shen, A Rosenberg, Z Qin, D Calandriello, M Khalman, ... ICLR 2025, 2025 | 15 | 2025 |
| Knowledge Distillation with Perturbed Loss: From a Vanilla Teacher to a Proxy Teacher R Zhang, J Shen, T Liu, J Liu, M Bendersky, M Najork, C Zhang Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 15* | 2024 |
| Offline regularised reinforcement learning for large language models alignment PH Richemond, Y Tang, D Guo, D Calandriello, MG Azar, R Rafailov, ... arXiv preprint arXiv:2405.19107, 2024 | 12 | 2024 |
| Clustering high-dimensional data via feature selection T Liu, Y Lu, B Zhu, H Zhao Biometrics 79 (2), 940-950, 2023 | 11 | 2023 |
| Direct language model alignment from online ai feedback, 2024 S Guo, B Zhang, T Liu, T Liu, M Khalman, F Llinares, A Rame, T Mesnard, ... URL https://arxiv. org/abs/2402.04792, 0 | 9 | |
| Predicting Text Preference Via Structured Comparative Reasoning JN Yan, T Liu, J Chiu, J Shen, Z Qin, Y Yu, C Lakshmanan, Y Kurzion, ... Proceedings of the 62nd Annual Meeting of the Association for Computational …, 2024 | 8* | 2024 |
| Training ELECTRA augmented with multi-word selection J Shen, J Liu, T Liu, C Yu, J Han Findings of ACL 2021, 2021 | 8 | 2021 |
| Ultrahigh dimensional feature selection via kernel canonical correlation analysis T Liu, KY Lee, H Zhao arXiv preprint arXiv:1604.07354, 2016 | 7 | 2016 |
| BERT for large-scale video segment classification with test-time augmentation T Liu, Q Shao ICCV 2019 Workshop, 2019 | 6 | 2019 |
Jiaming ShenGoogle DeepMindכתובת אימייל מאומתת בדומיין google.com