| Dreamcoder: growing generalizable, interpretable knowledge with wake–sleep bayesian program learning K Ellis, L Wong, M Nye, M Sable-Meyer, L Cary, L Anaya Pozo, L Hewitt, ... Philosophical Transactions of the Royal Society A 381 (2251), 20220050, 2023 | 185 | 2023 |
| Dreamcoder: Bootstrapping inductive program synthesis with wake-sleep library learning K Ellis, C Wong, M Nye, M Sablé-Meyer, L Morales, L Hewitt, L Cary, ... Proceedings of the 42nd acm sigplan international conference on programming …, 2021 | 149 | 2021 |
| Transfer learning with neural automl C Wong, N Houlsby, Y Lu, A Gesmundo Advances in neural information processing systems 31, 2018 | 125 | 2018 |
| A rapid molecular approach for chromosomal phasing JF Regan, N Kamitaki, T Legler, S Cooper, N Klitgord, G Karlin-Neumann, ... PloS one 10 (3), e0118270, 2015 | 88 | 2015 |
| Leveraging language to learn program abstractions and search heuristics C Wong, KM Ellis, J Tenenbaum, J Andreas International conference on machine learning, 11193-11204, 2021 | 51 | 2021 |
| Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks KM Collins, C Wong, J Feng, M Wei, JB Tenenbaum arXiv preprint arXiv:2205.05718, 2022 | 45 | 2022 |
| 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 | 42 | 2022 |
| From word models to world models: Translating from natural language to the probabilistic language of thought L Wong, G Grand, AK Lew, ND Goodman, VK Mansinghka, J Andreas, ... arXiv preprint arXiv:2306.12672, 2023 | 38 | 2023 |
| Cell-phone compatible wireless stethoscope C Wong US Patent App. 13/326,927, 2012 | 32 | 2012 |
| Top-down synthesis for library learning M Bowers, TX Olausson, L Wong, G Grand, JB Tenenbaum, K Ellis, ... Proceedings of the ACM on Programming Languages 7 (POPL), 1182-1213, 2023 | 30 | 2023 |
| Dancin seq2seq: Fooling text classifiers with adversarial text example generation C Wong arXiv preprint arXiv:1712.05419, 2017 | 29 | 2017 |
| Evaluating language models for mathematics through interactions KM Collins, AQ Jiang, S Frieder, L Wong, M Zilka, U Bhatt, T Lukasiewicz, ... arXiv preprint arXiv:2306.01694, 2023 | 14 | 2023 |
| Identifying concept libraries from language about object structure C Wong, WP McCarthy, G Grand, Y Friedman, JB Tenenbaum, J Andreas, ... arXiv preprint arXiv:2205.05666, 2022 | 14 | 2022 |
| Transfer automatic machine learning C Wong, N Houlsby, Y Lu, A Gesmundo arXiv preprint arXiv:1803.02780 2, 2018 | 9 | 2018 |
| Evaluating statistical language models as pragmatic reasoners B Lipkin, L Wong, G Grand, JB Tenenbaum arXiv preprint arXiv:2305.01020, 2023 | 8 | 2023 |
| Transfer learning to learn with multitask neural model search C Wong, A Gesmundo arXiv preprint arXiv:1710.10776, 2017 | 7 | 2017 |
| The neuro-symbolic inverse planning engine (nipe): Modeling probabilistic social inferences from linguistic inputs L Ying, KM Collins, M Wei, CE Zhang, T Zhi-Xuan, A Weller, ... arXiv preprint arXiv:2306.14325, 2023 | 5 | 2023 |
| Grounded physical language understanding with probabilistic programs and simulated worlds C Zhang, L Wong, G Grand, J Tenenbaum Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45), 2023 | 5 | 2023 |
| 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 |
| Lilo: Learning interpretable libraries by compressing and documenting code G Grand, L Wong, M Bowers, TX Olausson, M Liu, JB Tenenbaum, ... arXiv preprint arXiv:2310.19791, 2023 | 3 | 2023 |
Joshua B. TenenbaumMITVerified email at mit.edu
