| Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... Journal of Machine Learning Research 24 (240), 1-113, 2023 | 4737 | 2023 |
| Deep learning based recommender system: A survey and new perspectives S Zhang, L Yao, A Sun, Y Tay ACM Computing Surveys, 2017 | 3549 | 2017 |
| Scaling instruction-finetuned language models HW Chung, L Hou, S Longpre, B Zoph, Y Tay, W Fedus, Y Li, X Wang, ... Journal of Machine Learning Research 25 (70), 1-53, 2024 | 2673 | 2024 |
| Emergent abilities of large language models J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... Transactions of Machine Learning Research (TMLR), 2022 | 2660* | 2022 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1321 | 2023 |
| Efficient Transformers: A Survey Y Tay, M Dehghani, D Bahri, D Metzler ACM Computing Surveys, 2022, 2022 | 1289* | 2022 |
| Long Range Arena: A Benchmark for Efficient Transformers Y Tay*, M Dehghani*, S Abnar, Y Shen, D Bahri, P Pham, J Rao, L Yang, ... ICLR 2021, 2020 | 618 | 2020 |
| Quaternion Knowledge Graph Embedding S Zhang*, Y Tay*, L Yao, Q Liu NeurIPS 2019, 2019 | 582 | 2019 |
| The flan collection: Designing data and methods for effective instruction tuning S Longpre, L Hou, T Vu, A Webson, HW Chung, Y Tay, D Zhou, QV Le, ... International Conference on Machine Learning, 22631-22648, 2023 | 528 | 2023 |
| Challenging big-bench tasks and whether chain-of-thought can solve them M Suzgun, N Scales, N Schärli, S Gehrmann, Y Tay, HW Chung, ... arXiv preprint arXiv:2210.09261, 2022 | 470 | 2022 |
| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning, 7480-7512, 2023 | 401 | 2023 |
| UL2: Unifying Language Learning Paradigms Y Tay, M Dehghani, VQ Tran, X Garcia, J Wei, X Wang, HW Chung, ... ICLR 2023, 2022 | 382* | 2022 |
| Synthesizer: Rethinking self-attention in transformer models Y Tay, D Bahri, D Metzler, DC Juan, Z Zhao, C Zheng ICML 2021, 2020 | 374 | 2020 |
| Multi-Pointer Co-Attention Networks for Recommendation Y Tay, LA Tuan, SC Hui KDD 2018, 2018 | 354 | 2018 |
| Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking Y Tay, LA Tuan, SC Hui Proceedings of WWW 2018, 2018 | 344 | 2018 |
| Sparse Sinkhorn Attention Y Tay, D Bahri, L Yang, D Metzler, DC Juan ICML 2020, 2020 | 324 | 2020 |
| Next item recommendation with self-attention S Zhang, Y Tay, L Yao, A Sun arXiv preprint arXiv:1808.06414, 2018 | 262* | 2018 |
| Dive into Deep Learning: Recommender Systems S Zhang, A Zhang, Y Tay | 244* | 2019 |
| Larger language models do in-context learning differently J Wei, J Wei, Y Tay, D Tran, A Webson, Y Lu, X Chen, H Liu, D Huang, ... arXiv preprint arXiv:2303.03846, 2023 | 231 | 2023 |
| Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysis Y Tay, AT Luu, SC Hui Proceedings of AAAI 2018, 2018 | 212 | 2018 |
Donald MetzlerGoogle DeepMind在 google.com 的电子邮件经过验证
