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 | 2453 | 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 | 958 | 2024 |
Chlorpyrifos degradation by the cyanobacterium Synechocystis sp. strain PUPCCC 64 DP Singh, JIS Khattar, J Nadda, Y Singh, A Garg, N Kaur, A Gulati Environmental Science and Pollution Research 18, 1351-1359, 2011 | 150 | 2011 |
A comparative evaluation of ear diseases in children of higher versus lower socioeconomic status SK Chadha, AK Agarwal, A Gulati, A Garg The Journal of Laryngology & Otology 120 (1), 16-19, 2006 | 63 | 2006 |
Do current multi-task optimization methods in deep learning even help? D Xin, B Ghorbani, J Gilmer, A Garg, O Firat Advances in neural information processing systems 35, 13597-13609, 2022 | 61 | 2022 |
The devil is in the errors: Leveraging large language models for fine-grained machine translation evaluation P Fernandes, D Deutsch, M Finkelstein, P Riley, AFT Martins, G Neubig, ... Association for Computational Linguistics, 2023 | 60 | 2023 |
Machine translation: a literature review A Garg, M Agarwal arXiv preprint arXiv:1901.01122, 2018 | 53 | 2018 |
Data scaling laws in NMT: The effect of noise and architecture Y Bansal, B Ghorbani, A Garg, B Zhang, C Cherry, B Neyshabur, O Firat International Conference on Machine Learning, 1466-1482, 2022 | 40 | 2022 |
A loss curvature perspective on training instabilities of deep learning models J Gilmer, B Ghorbani, A Garg, S Kudugunta, B Neyshabur, D Cardoze, ... International Conference on Learning Representations, 2022 | 39 | 2022 |
GROOV: A geographic routing over VANETs and its performance evaluation SK Dhurandher, MS Obaidat, D Bhardwaj, A Garg 2012 IEEE Global Communications Conference (GLOBECOM), 1670-1675, 2012 | 30 | 2012 |
Echo state speech recognition H Shrivastava, A Garg, Y Cao, Y Zhang, T Sainath ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 27 | 2021 |
Benchmarking neural network training algorithms GE Dahl, F Schneider, Z Nado, N Agarwal, CS Sastry, P Hennig, ... MLCommons AlgoPerf: Training Algorithms Benchmark, 2023 | 23 | 2023 |
Appendicitis in paraumbilical hernia mimicking strangulation: a case report and review of the literature N Agarwal, S Goyal, A Kumar, A Garg, N Kaur, A Gupta Hernia 17, 531-532, 2013 | 20 | 2013 |
Efficient and private federated learning with partially trainable networks H Sidahmed, Z Xu, A Garg, Y Cao, M Chen NeurIPS Workshop on New Frontiers in Federated Learning, 2021 | 16 | 2021 |
The geometry of integration in text classification RNNs K Aitken, VV Ramasesh, A Garg, Y Cao, D Sussillo, N Maheswaranathan International Conference on Learning Representations, 2020 | 14 | 2020 |
Binarized neural machine translation Y Zhang, A Garg, Y Cao, L Lew, B Ghorbani, Z Zhang, O Firat Advances in Neural Information Processing Systems 36, 2024 | 13 | 2024 |
Hands-on one-shot learning with python: Learn to implement fast and accurate deep learning models with fewer training samples using pytorch S Jadon, A Garg Packt Publishing Ltd, 2020 | 13 | 2020 |
Wormhole attack prevention using clustering and digital signatures in reactive routing A Malhotra, D Bhardwaj, A Garg Proceedings of 2012 9th IEEE International Conference on Networking, Sensing …, 2012 | 10 | 2012 |
Order matters in the presence of dataset imbalance for multilingual learning D Choi, D Xin, H Dadkhahi, J Gilmer, A Garg, O Firat, CK Yeh, AM Dai, ... Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
Echo state neural machine translation A Garg, Y Cao, Q Ge arXiv preprint arXiv:2002.11847, 2020 | 4 | 2020 |