| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 763 | 2023 |
| 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 | 419 | 2023 |
| The creation and analysis of a website privacy policy corpus S Wilson, F Schaub, AA Dara, F Liu, S Cherivirala, PG Leon, ... Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 328* | 2016 |
| Estimating training data influence by tracing gradient descent G Pruthi, F Liu, M Sundararajan, S Kale Advances in Neural Information Processing Systems 33, 2020 | 250 | 2020 |
| Attention-based multimodal neural machine translation PY Huang, F Liu, SR Shiang, J Oh, C Dyer Proceedings of the First Conference on Machine Translation: Volume 2, Shared …, 2016 | 217 | 2016 |
| Crowdsourcing annotations for websites' privacy policies: Can it really work? S Wilson, F Schaub, R Ramanath, N Sadeh, F Liu, NA Smith, F Liu Proceedings of the 25th International Conference on World Wide Web, 133-143, 2016 | 118 | 2016 |
| Incorporating Priors with Feature Attribution on Text Classification F Liu, B Avci ACL 2019, 2019 | 113 | 2019 |
| TensorFlow model garden H Yu, C Chen, X Du, Y Li, A Rashwan, L Hou, P Jin, F Yang, F Liu, J Kim, ... Model Garden for TensorFlow., 2020 | 82 | 2020 |
| Learning character-level compositionality with visual features F Liu, H Lu, C Lo, G Neubig ACL 2017, 2017 | 78 | 2017 |
| Handling homographs in neural machine translation F Liu, H Lu, G Neubig NAACL 2018, 2017 | 67 | 2017 |
| Analyzing privacy policies at scale: From crowdsourcing to automated annotations S Wilson, F Schaub, F Liu, KM Sathyendra, D Smullen, S Zimmeck, ... ACM Transactions on the Web (TWEB) 13 (1), 1-29, 2018 | 61* | 2018 |
| Detecting errors and estimating accuracy on unlabeled data with self-training ensembles J Chen, F Liu, B Avci, X Wu, Y Liang, S Jha Advances in Neural Information Processing Systems 34, 14980-14992, 2021 | 57 | 2021 |
| Differentially-private" draw and discard" machine learning V Pihur, A Korolova, F Liu, S Sankuratripati, M Yung, D Huang, R Zeng arXiv preprint arXiv:1807.04369, 2018 | 51* | 2018 |
| Towards tracing factual knowledge in language models back to the training data E Akyürek, T Bolukbasi, F Liu, B Xiong, I Tenney, J Andreas, K Guu arXiv preprint arXiv:2205.11482, 2022 | 44 | 2022 |
| EncT5: A Framework for Fine-tuning T5 as Non-autoregressive Models F Liu, T Huang, S Lyu, S Shakeri, H Yu, J Li arXiv preprint arXiv:2110.08426, 2021 | 19* | 2021 |
| Leveraging redundancy in attention with reuse transformers S Bhojanapalli, A Chakrabarti, A Veit, M Lukasik, H Jain, F Liu, YW Chang, ... arXiv preprint arXiv:2110.06821, 2021 | 18 | 2021 |
| First is Better Than Last for Language Data Influence CK Yeh, A Taly, M Sundararajan, F Liu, PK Ravikumar Advances in Neural Information Processing Systems, 2022 | 15* | 2022 |
| Chefs' random tables: Non-trigonometric random features V Likhosherstov, KM Choromanski, KA Dubey, F Liu, T Sarlos, A Weller Advances in Neural Information Processing Systems 35, 34559-34573, 2022 | 10 | 2022 |
| Threading the needle of on and off-manifold value functions for shapley explanations CK Yeh, KY Lee, F Liu, P Ravikumar International Conference on Artificial Intelligence and Statistics, 1485-1502, 2022 | 9 | 2022 |
| 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 | 6 | 2024 |
