| 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 | 726 | 2024 |
| A graph placement methodology for fast chip design A Mirhoseini, A Goldie, M Yazgan, JW Jiang, E Songhori, S Wang, YJ Lee, ... Nature 594 (7862), 207-212, 2021 | 687* | 2021 |
| Using deep learning to enhance cancer diagnosis and classification R Fakoor, F Ladhak, A Nazi, M Huber The 30th International Conference on Machine Learning (ICML 2013), WHEALTH …, 2013 | 671 | 2013 |
| Chip placement with deep reinforcement learning A Mirhoseini, A Goldie, M Yazgan, J Jiang, E Songhori, S Wang, YJ Lee, ... arXiv preprint arXiv:2004.10746, 2020 | 258 | 2020 |
| Selectivity estimation for range predicates using lightweight models A Dutt, C Wang, A Nazi, S Kandula, V Narasayya, S Chaudhuri Proceedings of the VLDB Endowment 12 (9), 1044-1057, 2019 | 222* | 2019 |
| Teaching algorithmic reasoning via in-context learning H Zhou, A Nova, H Larochelle, A Courville, B Neyshabur, H Sedghi arXiv preprint arXiv:2211.09066, 2022 | 104* | 2022 |
| Scalable deep generative modeling for sparse graphs H Dai, A Nazi, Y Li, B Dai, D Schuurmans International conference on machine learning, 2302-2312, 2020 | 79 | 2020 |
| Gap: Generalizable approximate graph partitioning framework A Nazi, W Hang, A Goldie, S Ravi, A Mirhoseini arXiv preprint arXiv:1903.00614, 2019 | 77 | 2019 |
| Many-shot in-context learning R Agarwal, A Singh, LM Zhang, B Bohnet, L Rosias, S Chan, B Zhang, ... arXiv preprint arXiv:2404.11018, 2024 | 67* | 2024 |
| Beyond human data: Scaling self-training for problem-solving with language models A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, X Garcia, PJ Liu, ... arXiv preprint arXiv:2312.06585, 2023 | 67 | 2023 |
| Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative A Asudeh, A Nazi, N Zhang, G Das Proceedings of the 2017 International Conference on Management of Data (SIGMOD), 2017 | 57 | 2017 |
| Walk, Not Wait: Faster Sampling Over Online Social Networks A Nazi, Z Zhou, S Thirumuruganathan, N Zhang, G Das http://arxiv.org/abs/1410.7833, 2014 | 40 | 2014 |
| An integrated cloud-based framework for mobile phone sensing R Fakoor, M Raj, A Nazi, M Di Francesco, SK Das Proceedings of the first edition of the MCC workshop on Mobile cloud …, 2012 | 35 | 2012 |
| Deployment of robust wireless sensor networks using gene regulatory networks: An isomorphism-based approach A Nazi, M Raj, M Di Francesco, P Ghosh, SK Das Pervasive and Mobile Computing 13, 246-257, 2014 | 30 | 2014 |
| RRR: Rank-regret representative A Asudeh, A Nazi, N Zhang, G Das, HV Jagadish Proceedings of the 2019 International Conference on Management of Data, 263-280, 2019 | 28* | 2019 |
| Efficient estimation of inclusion coefficient using hyperloglog sketches A Nazi, B Ding, V Narasayya, S Chaudhuri Proceedings of the VLDB Endowment 11 (10), 1097-1109, 2018 | 22 | 2018 |
| Efficient communications in wireless sensor networks based on biological robustness A Nazi, M Raj, M Di Francesco, P Ghosh, SK Das 2016 International Conference on Distributed Computing in Sensor Systems …, 2016 | 22 | 2016 |
| Robust deployment of wireless sensor networks using gene regulatory networks A Nazi, M Raj, M Di Francesco, P Ghosh, SK Das Distributed Computing and Networking: 14th International Conference, ICDCN …, 2013 | 22 | 2013 |
| NATURAL PLAN: Benchmarking LLMs on Natural Language Planning HS Zheng, S Mishra, H Zhang, X Chen, M Chen, A Nova, L Hou, ... arXiv preprint arXiv:2406.04520, 2024 | 14* | 2024 |
| Revisiting sampling for combinatorial optimization H Sun, K Goshvadi, A Nova, D Schuurmans, H Dai International Conference on Machine Learning, 32859-32874, 2023 | 14 | 2023 |
Anna GoldieGoogle DeepMind / StanfordVerified email at google.com
