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 | 1144 | 2022 |
An intriguing failing of convolutional neural networks and the coordconv solution R Liu, J Lehman, P Molino, F Petroski Such, E Frank, A Sergeev, ... Advances in neural information processing systems 31, 2018 | 1023 | 2018 |
Plug and play language models: A simple approach to controlled text generation S Dathathri, A Madotto, J Lan, J Hung, E Frank, P Molino, J Yosinski, ... arXiv preprint arXiv:1912.02164, 2019 | 969 | 2019 |
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 | 552 | 2024 |
Deconstructing lottery tickets: Zeros, signs, and the supermask H Zhou, J Lan, R Liu, J Yosinski Advances in neural information processing systems 32, 2019 | 467 | 2019 |
Measuring the intrinsic dimension of objective landscapes C Li, H Farkhoor, R Liu, J Yosinski arXiv preprint arXiv:1804.08838, 2018 | 402 | 2018 |
Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations L Ward, R Liu, A Krishna, VI Hegde, A Agrawal, A Choudhary, ... Physical Review B 96 (2), 024104, 2017 | 398 | 2017 |
A predictive machine learning approach for microstructure optimization and materials design R Liu, A Kumar, Z Chen, A Agrawal, V Sundararaghavan, A Choudhary Scientific reports 5 (1), 11551, 2015 | 386 | 2015 |
Supermasks in superposition M Wortsman, V Ramanujan, R Liu, A Kembhavi, M Rastegari, J Yosinski, ... Advances in Neural Information Processing Systems 33, 15173-15184, 2020 | 303 | 2020 |
Faster neural networks straight from jpeg L Gueguen, A Sergeev, B Kadlec, R Liu, J Yosinski Advances in Neural Information Processing Systems 31, 2018 | 262 | 2018 |
What does a platypus look like? generating customized prompts for zero-shot image classification S Pratt, I Covert, R Liu, A Farhadi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 200 | 2023 |
A Machine Learning-Based Design Representation Method for Designing Heterogeneous Microstructures H Xu, R Liu, A Choudhary, W Chen Journal of Mechanical Design 137 (5), 051403, 2015 | 165 | 2015 |
A Machine Learning-Based Design Representation Method for Designing Heterogeneous Microstructures H Xu, R Liu, A Choudhary, W Chen ASME International Design Engineering Technical Conferences, 2014 | 165 | 2014 |
Extremely simple activation shaping for out-of-distribution detection A Djurisic, N Bozanic, A Ashok, R Liu arXiv preprint arXiv:2209.09858, 2022 | 131 | 2022 |
Language models are few-shot multilingual learners GI Winata, A Madotto, Z Lin, R Liu, J Yosinski, P Fung arXiv preprint arXiv:2109.07684, 2021 | 123 | 2021 |
Machine learning approaches for elastic localization linkages in high-contrast composite materials R Liu, YC Yabansu, A Agrawal, SR Kalidindi, AN Choudhary Integrating Materials and Manufacturing Innovation 4, 192-208, 2015 | 111 | 2015 |
A scalable hierarchical clustering algorithm using spark C Jin, R Liu, Z Chen, W Hendrix, A Agrawal, A Choudhary 2015 IEEE First International Conference on Big Data Computing Service and …, 2015 | 73 | 2015 |
Context aware machine learning approaches for modeling elastic localization in three-dimensional composite microstructures R Liu, YC Yabansu, Z Yang, AN Choudhary, SR Kalidindi, A Agrawal Integrating Materials and Manufacturing Innovation 6, 160-171, 2017 | 72 | 2017 |
An atari model zoo for analyzing, visualizing, and comparing deep reinforcement learning agents FP Such, V Madhavan, R Liu, R Wang, PS Castro, Y Li, J Zhi, L Schubert, ... arXiv preprint arXiv:1812.07069, 2018 | 64 | 2018 |
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 | 63 | 2023 |