| Training complex models with multi-task weak supervision A Ratner, B Hancock, J Dunnmon, F Sala, S Pandey, C Ré Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4763-4771, 2019 | 231 | 2019 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 220 | 2024 |
| Learning from dialogue after deployment: Feed yourself, chatbot! B Hancock, A Bordes, PE Mazare, J Weston arXiv preprint arXiv:1901.05415, 2019 | 220 | 2019 |
| Training classifiers with natural language explanations B Hancock, M Bringmann, P Varma, P Liang, S Wang, C Ré Proceedings of the conference. Association for Computational Linguistics …, 2018 | 174 | 2018 |
| Snorkel drybell: A case study in deploying weak supervision at industrial scale SH Bach, D Rodriguez, Y Liu, C Luo, H Shao, C Xia, S Sen, A Ratner, ... Proceedings of the 2019 International Conference on Management of Data, 362-375, 2019 | 165 | 2019 |
| Fonduer: Knowledge base construction from richly formatted data S Wu, L Hsiao, X Cheng, B Hancock, T Rekatsinas, P Levis, C Ré Proceedings of the 2018 international conference on management of data, 1301 …, 2018 | 117 | 2018 |
| Snorkel metal: Weak supervision for multi-task learning A Ratner, B Hancock, J Dunnmon, R Goldman, C Ré Proceedings of the Second Workshop on Data Management for End-To-End Machine …, 2018 | 64 | 2018 |
| Language models in the loop: Incorporating prompting into weak supervision R Smith, JA Fries, B Hancock, SH Bach ACM/JMS Journal of Data Science 1 (2), 1-30, 2024 | 40 | 2024 |
| A Machine-Compiled Database of Genome-Wide Association Studies V Kuleshov, J Ding, B Hancock, A Ratner, C Ré, S Batzoglou, M Snyder Bio-Ontologies 2017, 2017 | 40 | 2017 |
| After Sandy Hook Elementary: A year in the gun control debate on Twitter A Benton, B Hancock, G Coppersmith, JW Ayers, M Dredze arXiv preprint arXiv:1610.02060, 2016 | 37 | 2016 |
| The Smart Normal Constraint Method for Directly Generating a Smart Pareto Set BJ Hancock, CA Mattson Structural and Multidisciplinary Optimization, 1-13, 2013 | 34 | 2013 |
| Collective supervision of topic models for predicting surveys with social media A Benton, M Paul, B Hancock, M Dredze Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 32 | 2016 |
| Computing on masked data to improve the security of big data V Gadepally, B Hancock, B Kaiser, J Kepner, P Michaleas, M Varia, ... 2015 IEEE International Symposium on Technologies for Homeland Security (HST …, 2015 | 30 | 2015 |
| The Role of Massively Multi-Task and Weak Supervision in Software 2.0. AJ Ratner, B Hancock, C Ré CIDR, 2019 | 29 | 2019 |
| Generating titles for web tables B Hancock, H Lee, C Yu The World Wide Web Conference, 638-647, 2019 | 28 | 2019 |
| Recommender Systems for the Department of Defense and Intelligence Community V Gadepally, B Hancock, K Greenfield, J Campbell, W Campbell, ... The Lincoln Laboratory Journal 22 (1), 74-89, 2016 | 27 | 2016 |
| Reducing shock interactions in transonic turbine via three-dimensional aerodynamic shaping BJ Hancock, JP Clark Journal of Propulsion and Power 30 (5), 1248-1256, 2014 | 12 | 2014 |
| Usage scenarios for design space exploration with a dynamic multiobjective optimization formulation SK Curtis, BJ Hancock, CA Mattson Research in Engineering Design 24, 395-409, 2013 | 11 | 2013 |
| Divergent exploration in design with a dynamic multiobjective optimization formulation SK Curtis, CA Mattson, BJ Hancock, PK Lewis Structural and Multidisciplinary Optimization 47 (5), 645-657, 2012 | 9 | 2012 |
| DMLR: Data-centric Machine Learning Research--Past, Present and Future L Oala, M Maskey, L Bat-Leah, A Parrish, NM Gürel, TS Kuo, Y Liu, R Dror, ... arXiv preprint arXiv:2311.13028, 2023 | 8 | 2023 |
Christopher RéComputer Science, Stanford UniversityVerified email at cs.stanford.edu
