| 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 | 1165 | 2022 |
| Starcoder: may the source be with you! R Li, LB Allal, Y Zi, N Muennighoff, D Kocetkov, C Mou, M Marone, C Akiki, ... arXiv preprint arXiv:2305.06161, 2023 | 857* | 2023 |
| Uniq: Uniform noise injection for non-uniform quantization of neural networks C Baskin, N Liss, E Schwartz, E Zheltonozhskii, R Giryes, AM Bronstein, ... ACM Transactions on Computer Systems (TOCS) 37 (1-4), 1-15, 2021 | 191* | 2021 |
| Loss aware post-training quantization Y Nahshan, B Chmiel, C Baskin, E Zheltonozhskii, R Banner, ... Machine Learning 110 (11), 3245-3262, 2021 | 177 | 2021 |
| End-to-end referring video object segmentation with multimodal transformers A Botach, E Zheltonozhskii, C Baskin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 142 | 2022 |
| Starcoder 2 and the stack v2: The next generation A Lozhkov, R Li, LB Allal, F Cassano, J Lamy-Poirier, N Tazi, A Tang, ... arXiv preprint arXiv:2402.19173, 2024 | 135 | 2024 |
| Contrast to divide: Self-supervised pre-training for learning with noisy labels E Zheltonozhskii, C Baskin, A Mendelson, AM Bronstein, O Litany Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 106 | 2022 |
| Nice: Noise injection and clamping estimation for neural network quantization C Baskin, E Zheltonozhkii, T Rozen, N Liss, Y Chai, E Schwartz, R Giryes, ... Mathematics 9 (17), 2144, 2021 | 70 | 2021 |
| Streaming architecture for large-scale quantized neural networks on an FPGA-based dataflow platform C Baskin, N Liss, E Zheltonozhskii, AM Bronstein, A Mendelson 2018 IEEE International Parallel and Distributed Processing Symposium …, 2018 | 61 | 2018 |
| Feature map transform coding for energy-efficient CNN inference B Chmiel, C Baskin, E Zheltonozhskii, R Banner, Y Yermolin, ... 2020 International Joint Conference on Neural Networks (IJCNN), 1-9, 2020 | 27 | 2020 |
| Early-stage neural network hardware performance analysis A Karbachevsky, C Baskin, E Zheltonozhskii, Y Yermolin, F Gabbay, ... Sustainability 13 (2), 717, 2021 | 21* | 2021 |
| Single-node attacks for fooling graph neural networks B Finkelshtein, C Baskin, E Zheltonozhskii, U Alon Neurocomputing 513, 1-12, 2022 | 18 | 2022 |
| CAT: Compression-Aware Training for bandwidth reduction C Baskin, B Chmiel, E Zheltonozhskii, R Banner, AM Bronstein, ... Journal of Machine Learning Research 22 (269), 1-20, 2021 | 12 | 2021 |
| Self-supervised learning for large-scale unsupervised image clustering E Zheltonozhskii, C Baskin, AM Bronstein, A Mendelson arXiv preprint arXiv:2008.10312, 2020 | 10 | 2020 |
| Semi-Supervised Semantic Segmentation via Marginal Contextual Information M Kimhi, S Kimhi, E Zheltonozhskii, O Litany, C Baskin arXiv preprint arXiv:2308.13900, 2023 | 7 | 2023 |
| Adversarial robustness via noise injection in smoothed models Y Nemcovsky, E Zheltonozhskii, C Baskin, B Chmiel, AM Bronstein, ... Applied Intelligence 53 (8), 9483-9498, 2023 | 7* | 2023 |
| Colored noise injection for training adversarially robust neural networks E Zheltonozhskii, C Baskin, Y Nemcovsky, B Chmiel, A Mendelson, ... arXiv preprint arXiv:2003.02188, 2020 | 7 | 2020 |
| Towards learning of filter-level heterogeneous compression of convolutional neural networks Y Zur, C Baskin, E Zheltonozhskii, B Chmiel, I Evron, AM Bronstein, ... arXiv preprint arXiv:1904.09872, 2019 | 6 | 2019 |
| Identifying the topological order of quantized half-filled Landau levels through their daughter states E Zheltonozhskii, A Stern, N Lindner arXiv preprint arXiv:2405.03780, 2024 | 3 | 2024 |
| System and method for emulating quantization noise for a neural network C Baskin, E Schwartz, E Zheltonozhskii, A Bronstein, L Natan, ... US Patent 11,972,347, 2024 | 3 | 2024 |
Chaim BaskinAssistant Professor (Senior Lecturer) at Ben-Gurion University of the NegevVerified email at bgu.ac.il
