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 | 3570 | 2023 |
Towards a human-like open-domain chatbot D Adiwardana, MT Luong, DR So, J Hall, N Fiedel, R Thoppilan, Z Yang, ... arXiv preprint arXiv:2001.09977, 2020 | 1037 | 2020 |
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 758 | 2022 |
Tfx: A tensorflow-based production-scale machine learning platform D Baylor, E Breck, HT Cheng, N Fiedel, CY Foo, Z Haque, S Haykal, ... Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 450 | 2017 |
Tensorflow-serving: Flexible, high-performance ml serving C Olston, N Fiedel, K Gorovoy, J Harmsen, L Lao, F Li, V Rajashekhar, ... arXiv preprint arXiv:1712.06139, 2017 | 309 | 2017 |
Wt5?! training text-to-text models to explain their predictions S Narang, C Raffel, K Lee, A Roberts, N Fiedel, K Malkan arXiv preprint arXiv:2004.14546, 2020 | 173 | 2020 |
Talm: Tool augmented language models A Parisi, Y Zhao, N Fiedel arXiv preprint arXiv:2205.12255, 2022 | 117 | 2022 |
Scaling up models and data with t5x and seqio A Roberts, HW Chung, G Mishra, A Levskaya, J Bradbury, D Andor, ... Journal of Machine Learning Research 24 (377), 1-8, 2023 | 116 | 2023 |
Do transformer modifications transfer across implementations and applications? S Narang, HW Chung, Y Tay, W Fedus, T Fevry, M Matena, K Malkan, ... arXiv preprint arXiv:2102.11972, 2021 | 108* | 2021 |
Storage and distribution of content for a user device group V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,438,233, 2013 | 98 | 2013 |
Sharing content among a group of devices V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,386,619, 2013 | 82 | 2013 |
User device group formation V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,539,086, 2013 | 78 | 2013 |
Pushing tuning parameters for logical group scoring V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,892,653, 2014 | 68 | 2014 |
Sharing content among multiple devices V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,392,526, 2013 | 58 | 2013 |
Gemma: Open models based on gemini research and technology G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ... arXiv preprint arXiv:2403.08295, 2024 | 54 | 2024 |
Understanding html with large language models I Gur, O Nachum, Y Miao, M Safdari, A Huang, A Chowdhery, S Narang, ... arXiv preprint arXiv:2210.03945, 2022 | 42 | 2022 |
Determining logical groups based on both passive and active activities of user V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,959,153, 2015 | 37 | 2015 |
Elastic logical groups V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,930,459, 2015 | 37 | 2015 |
Adding user to logical group based on content V Mallet, J Cheng, N Fiedel, EW Gillum, G Ramanarayanan, NJ Woods US Patent 8,972,501, 2015 | 36 | 2015 |
Batching inputs to a machine learning model N Fiedel, C Olston, J Harmsen US Patent 10,789,544, 2020 | 35 | 2020 |