| 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 | 3208 | 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 | 1170 | 2024 |
| TAPAS: Weakly Supervised Table Parsing via Pre-training J Herzig, PK Nowak, T Müller, F Piccinno, JM Eisenschlos Proceedings of ACL 2020, 2020 | 660 | 2020 |
| Pix2struct: Screenshot parsing as pretraining for visual language understanding K Lee, M Joshi, IR Turc, H Hu, F Liu, JM Eisenschlos, U Khandelwal, ... International Conference on Machine Learning, 18893-18912, 2023 | 264 | 2023 |
| Time-aware language models as temporal knowledge bases B Dhingra, JR Cole, JM Eisenschlos, D Gillick, J Eisenstein, WW Cohen Transactions of the Association for Computational Linguistics 10, 257-273, 2022 | 254 | 2022 |
| Paligemma: A versatile 3b vlm for transfer L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... arXiv preprint arXiv:2407.07726, 2024 | 131 | 2024 |
| Understanding tables with intermediate pre-training JM Eisenschlos, S Krichene, T Müller Findings of EMNLP 2020, 2020 | 119 | 2020 |
| Multifit: Efficient multi-lingual language model fine-tuning JM Eisenschlos, S Ruder, P Czapla, M Kardas, S Gugger, J Howard Proceedings of EMNLP 2020, 2019 | 114 | 2019 |
| Open Domain Question Answering over Tables via Dense Retrieval J Herzig, T Müller, S Krichene, JM Eisenschlos Proceedings of NAACL 2021, 2021 | 98 | 2021 |
| Deplot: One-shot visual language reasoning by plot-to-table translation F Liu, JM Eisenschlos, F Piccinno, S Krichene, C Pang, K Lee, M Joshi, ... arXiv preprint arXiv:2212.10505, 2022 | 91 | 2022 |
| MATE: Multi-view attention for table transformer efficiency JM Eisenschlos, M Gor, T Mueller, W Cohen Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 88 | 2021 |
| Chain-of-table: Evolving tables in the reasoning chain for table understanding Z Wang, H Zhang, CL Li, JM Eisenschlos, V Perot, Z Wang, L Miculicich, ... arXiv preprint arXiv:2401.04398, 2024 | 83 | 2024 |
| Matcha: Enhancing visual language pretraining with math reasoning and chart derendering F Liu, F Piccinno, S Krichene, C Pang, K Lee, M Joshi, Y Altun, N Collier, ... arXiv preprint arXiv:2212.09662, 2022 | 80 | 2022 |
| SoftSort: A Continuous Relaxation for the argsort Operator S Prillo, JM Eisenschlos Proceedings of ICML 2020, 2020 | 71 | 2020 |
| Selectively answering ambiguous questions JR Cole, MJQ Zhang, D Gillick, JM Eisenschlos, B Dhingra, J Eisenstein arXiv preprint arXiv:2305.14613, 2023 | 55 | 2023 |
| Fool Me Twice: Entailment from Wikipedia Gamification JM Eisenschlos, B Dhingra, J Bulian, B Börschinger, J Boyd-Graber Proceedings of NAACL 2021, 2021 | 39 | 2021 |
| Table-to-text generation and pre-training with tabt5 E Andrejczuk, JM Eisenschlos, F Piccinno, S Krichene, Y Altun arXiv preprint arXiv:2210.09162, 2022 | 31 | 2022 |
| Modifying text according to a specified attribute TL Julian Martin Eisenschlos US Patent App. 16/699,825, 2021 | 30* | 2021 |
| Universal self-adaptive prompting X Wan, R Sun, H Nakhost, H Dai, JM Eisenschlos, SO Arik, T Pfister arXiv preprint arXiv:2305.14926, 2023 | 20 | 2023 |
| DoT: An efficient Double Transformer for NLP tasks with tables S Krichene, T Müller, JM Eisenschlos Findings of ACL 2021, 2021 | 15 | 2021 |
Francesco PiccinnoGoogle DeepMindยืนยันอีเมลแล้วที่ google.com