| How is chatgpt’s behavior changing over time? L Chen, M Zaharia, J Zou arXiv preprint arXiv.2307.09009, 2023 | 326 | 2023 |
| Draco: Byzantine-resilient distributed training via redundant gradients L Chen, H Wang, Z Charles, D Papailiopoulos International Conference on Machine Learning, 903-912, 2018 | 282* | 2018 |
| Towards model-based pricing for machine learning in a data marketplace L Chen, P Koutris, A Kumar Proceedings of the 2019 international conference on management of data, 1535 …, 2019 | 130 | 2019 |
| Towards linear algebra over normalized data L Chen, A Kumar, J Naughton, JM Patel Proceedings of the VLDB Endowment 10 (11), 1214-1225, 2016 | 104 | 2016 |
| Frugalgpt: How to use large language models while reducing cost and improving performance L Chen, M Zaharia, J Zou arXiv preprint arXiv:2305.05176, 2023 | 102 | 2023 |
| Dataperf: Benchmarks for data-centric ai development M Mazumder, C Banbury, X Yao, B Karlaš, WG Rojas, S Diamos, ... Advances in neural information processing systems, 2023 | 93 | 2023 |
| Enabling and optimizing non-linear feature interactions in factorized linear algebra S Li, L Chen, A Kumar Proceedings of the 2019 International Conference on Management of Data, 1571 …, 2019 | 41 | 2019 |
| FrugalML: How to Use ML Prediction APIs more Accurately and Cheaply L Chen, M Zaharia, JY Zou Advances in neural information processing systems 33, 10685-10696, 2020 | 35 | 2020 |
| Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews W Liang, Z Izzo, Y Zhang, H Lepp, H Cao, X Zhao, L Chen, H Ye, S Liu, ... arXiv preprint arXiv:2403.07183, 2024 | 28 | 2024 |
| Tuple-oriented compression for large-scale mini-batch stochastic gradient descent F Li, L Chen, Y Zeng, A Kumar, X Wu, JF Naughton, JM Patel Proceedings of the 2019 International Conference on Management of Data, 1517 …, 2019 | 28 | 2019 |
| Reinforcing adversarial robustness using model confidence induced by adversarial training X Wu, U Jang, J Chen, L Chen, S Jha International conference on machine learning, 5334-5342, 2018 | 26 | 2018 |
| The shift from models to compound ai systems M Zaharia, O Khattab, L Chen, JQ Davis, H Miller, C Potts, J Zou, ... Berkeley Artificial Intelligence Research Lab. Available online at: https …, 2024 | 25 | 2024 |
| The effect of network width on the performance of large-batch training L Chen, H Wang, J Zhao, D Papailiopoulos, P Koutris Advances in neural information processing systems 31, 2018 | 24 | 2018 |
| How is ChatGPT’s behavior changing over time?(2023) L Chen, M Zaharia, J Zou arXiv preprint arXiv:2307.09009, 0 | 19 | |
| Efficient online ml api selection for multi-label classification tasks L Chen, M Zaharia, J Zou International conference on machine learning, 3716-3746, 2022 | 17* | 2022 |
| How Did the model change? Efficiently assessing machine learning API shifts L Chen, T Cai, M Zaharia, J Zou arXiv preprint arXiv:2107.14203, 2021 | 17 | 2021 |
| Distributed user-centric scheduling for visible light communication networks L Chen, J Wang, J Zhou, DWK Ng, R Schober, C Zhao Optics Express 24 (14), 15570-15589, 2016 | 17 | 2016 |
| Seal: Interactive tool for systematic error analysis and labeling N Rajani, W Liang, L Chen, M Mitchell, J Zou arXiv preprint arXiv:2210.05839, 2022 | 16 | 2022 |
| Estimating and explaining model performance when both covariates and labels shift L Chen, M Zaharia, JY Zou Advances in Neural Information Processing Systems 35, 11467-11479, 2022 | 15 | 2022 |
| When lempel-ziv-welch meets machine learning: A case study of accelerating machine learning using coding F Li, L Chen, A Kumar, JF Naughton, JM Patel, X Wu arXiv preprint arXiv:1702.06943, 2017 | 10 | 2017 |
