| ChemBERTa: large-scale self-supervised pretraining for molecular property prediction S Chithrananda, G Grand, B Ramsundar arXiv preprint arXiv:2010.09885, 2020 | 339 | 2020 |
| Semantic projection recovers rich human knowledge of multiple object features from word embeddings G Grand, IA Blank, F Pereira, E Fedorenko Nature human behaviour 6 (7), 975-987, 2022 | 122 | 2022 |
| Adversarial regularization for visual question answering: Strengths, shortcomings, and side effects G Grand, Y Belinkov arXiv preprint arXiv:1906.08430, 2019 | 73 | 2019 |
| Chemberta-2: Towards chemical foundation models W Ahmad, E Simon, S Chithrananda, G Grand, B Ramsundar arXiv preprint arXiv:2209.01712, 2022 | 64 | 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 | 39 | 2023 |
| 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 |
| 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 |
| ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction. 2020 S Chithrananda, G Grand, B Ramsundar URL https://arxiv. org/abs, 2010 | 13 | 2010 |
| Sequential monte carlo steering of large language models using probabilistic programs AK Lew, T Zhi-Xuan, G Grand, VK Mansinghka arXiv preprint arXiv:2306.03081, 2023 | 9 | 2023 |
| Evaluating statistical language models as pragmatic reasoners B Lipkin, L Wong, G Grand, JB Tenenbaum arXiv preprint arXiv:2305.01020, 2023 | 8 | 2023 |
| ChemBERTa-2: towards chemical foundation models. arXiv 2022 W Ahmad, E Simon, S Chithrananda, G Grand, B Ramsundar arXiv preprint arXiv:2209.01712, 0 | 7 | |
| Semantic projection recovers rich human knowledge of multiple object features from word embeddings. Nature Human Behaviour, 6 (7), 975-987 G Grand, IA Blank, F Pereira, E Fedorenko | 6 | 2022 |
| 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 |
| Chemberta: Large-scale self-supervised pretraining for molecular property predictionarXiv preprint S Chithrananda, G Grand, B Ramsundar arXiv preprint arXiv:2010.09885, 2020 | 5 | 2020 |
| 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 |
| Learning interpretable libraries by compressing and documenting code G Grand, L Wong, M Bowers, TX Olausson, M Liu, JB Tenenbaum, ... Intrinsically-Motivated and Open-Ended Learning Workshop@ NeurIPS2023, 2023 | 2 | 2023 |
| Stream of Search (SoS): Learning to Search in Language K Gandhi, D Lee, G Grand, M Liu, W Cheng, A Sharma, ND Goodman arXiv preprint arXiv:2404.03683, 2024 | | 2024 |
| Loose LIPS Sink Ships: Asking Questions in Battleship with Language-Informed Program Sampling G Grand, V Pepe, J Andreas, JB Tenenbaum arXiv preprint arXiv:2402.19471, 2024 | | 2024 |
| Discovering Abstractions from Language via Neurosymbolic Program Synthesis GJ Grand Massachusetts Institute of Technology, 2023 | | 2023 |
| Compounds, compositions and methods of treating disorders MR Spyvee, JM Kallenbach, A Gupta, E Simon, GJ Grand US Patent App. 17/744,228, 2022 | | 2022 |
Joshua B. TenenbaumMITVerified email at mit.edu
