| Verifiable reinforcement learning via policy extraction O Bastani, Y Pu, A Solar-Lezama Advances in neural information processing systems 31, 2018 | 358 | 2018 |
| Write, execute, assess: Program synthesis with a repl K Ellis, M Nye, Y Pu, F Sosa, J Tenenbaum, A Solar-Lezama Advances in Neural Information Processing Systems 32, 2019 | 154 | 2019 |
| Inversecsg: Automatic conversion of 3d models to csg trees T Du, JP Inala, Y Pu, A Spielberg, A Schulz, D Rus, A Solar-Lezama, ... ACM Transactions on Graphics (TOG) 37 (6), 1-16, 2018 | 153 | 2018 |
| Fusion 360 gallery: A dataset and environment for programmatic cad construction from human design sequences KDD Willis, Y Pu, J Luo, H Chu, T Du, JG Lambourne, A Solar-Lezama, ... ACM Transactions on Graphics (TOG) 40 (4), 1-24, 2021 | 109 | 2021 |
| sk_p: a neural program corrector for MOOCs Y Pu, K Narasimhan, A Solar-Lezama, R Barzilay Companion Proceedings of the 2016 ACM SIGPLAN International Conference on …, 2016 | 104 | 2016 |
| Engineering sketch generation for computer-aided design KDD Willis, PK Jayaraman, JG Lambourne, H Chu, Y Pu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 53 | 2021 |
| Synthesis of biological models from mutation experiments AS Koksal, Y Pu, S Srivastava, R Bodik, J Fisher, N Piterman Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of …, 2013 | 50 | 2013 |
| Communicating natural programs to humans and machines S Acquaviva, Y Pu, M Kryven, T Sechopoulos, C Wong, G Ecanow, M Nye, ... Advances in Neural Information Processing Systems 35, 3731-3743, 2022 | 45 | 2022 |
| Compiler auto-vectorization with imitation learning C Mendis, C Yang, Y Pu, DS Amarasinghe, M Carbin Advances in Neural Information Processing Systems 32, 2019 | 44 | 2019 |
| Neurosymbolic transformers for multi-agent communication JP Inala, Y Yang, J Paulos, Y Pu, O Bastani, V Kumar, M Rinard, ... Advances in Neural Information Processing Systems 33, 13597-13608, 2020 | 33 | 2020 |
| Hypothesis search: Inductive reasoning with language models R Wang, E Zelikman, G Poesia, Y Pu, N Haber, ND Goodman arXiv preprint arXiv:2309.05660, 2023 | 32 | 2023 |
| Program synthesis guided reinforcement learning for partially observed environments Y Yang, JP Inala, O Bastani, Y Pu, A Solar-Lezama, M Rinard Advances in neural information processing systems 34, 29669-29683, 2021 | 32 | 2021 |
| Selecting representative examples for program synthesis Y Pu, Z Miranda, A Solar-Lezama, L Kaelbling International Conference on Machine Learning, 4161-4170, 2018 | 31 | 2018 |
| Synthesis of first-order dynamic programming algorithms Y Pu, R Bodik, S Srivastava ACM SIGPLAN Notices 46 (10), 83-98, 2011 | 31 | 2011 |
| Representing partial programs with blended abstract semantics M Nye, Y Pu, M Bowers, J Andreas, JB Tenenbaum, A Solar-Lezama arXiv preprint arXiv:2012.12964, 2020 | 25 | 2020 |
| Fusion 360 gallery: A dataset and environment for programmatic cad reconstruction K Willis, Y Pu, J Luo, H Chu, T Du, J Lambourne, A Solar-Lezama, ... | 22 | 2020 |
| Program synthesis with pragmatic communication Y Pu, K Ellis, M Kryven, J Tenenbaum, A Solar-Lezama Advances in neural information processing systems 33, 13249-13259, 2020 | 21 | 2020 |
| Learning to acquire information Y Pu, LP Kaelbling, A Solar-Lezama arXiv preprint arXiv:1704.06131, 2017 | 5 | 2017 |
| Larc: Language annotated abstraction and reasoning corpus S Acquaviva, Y Pu, M Nye, C Wong, MH Tessler, J Tenenbaum Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | 4 | 2021 |
| Learning to select examples for program synthesis Y Pu, Z Miranda, A Solar-Lezama, LP Kaelbling | 4 | 2018 |
Armando Solar-LezamaMIT在 csail.mit.edu 的电子邮件经过验证
