| 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 | 749 | 2022 |
| Can language models learn from explanations in context? AK Lampinen, I Dasgupta, SCY Chan, K Matthewson, MH Tessler, ... arXiv preprint arXiv:2204.02329, 2022 | 197 | 2022 |
| Data distributional properties drive emergent in-context learning in transformers S Chan, A Santoro, A Lampinen, J Wang, A Singh, P Richemond, ... Advances in Neural Information Processing Systems 35, 18878-18891, 2022 | 178 | 2022 |
| Environmental drivers of systematicity and generalization in a situated agent F Hill, A Lampinen, R Schneider, S Clark, M Botvinick, JL McClelland, ... arXiv preprint arXiv:1910.00571, 2019 | 125* | 2019 |
| Language models show human-like content effects on reasoning I Dasgupta, AK Lampinen, SCY Chan, A Creswell, D Kumaran, ... arXiv preprint arXiv:2207.07051, 2022 | 119 | 2022 |
| What shapes feature representations? exploring datasets, architectures, and training KL Hermann, AK Lampinen Advances in Neural Information Processing Systems, 2020 | 119 | 2020 |
| An analytic theory of generalization dynamics and transfer learning in deep linear networks AK Lampinen, S Ganguli 7th International Conference on Learning Representations (ICLR 2019), 2018 | 108 | 2018 |
| Automated curricula through setter-solver interactions S Racaniere, AK Lampinen, A Santoro, DP Reichert, V Firoiu, TP Lillicrap 8th International Conference on Learning Representations (ICLR 2020), 2019 | 93* | 2019 |
| Integration of new information in memory: new insights from a complementary learning systems perspective JL McClelland, BL McNaughton, AK Lampinen Philosophical Transactions of the Royal Society B 375 (1799), 20190637, 2020 | 88 | 2020 |
| Semantic exploration from language abstractions and pretrained representations A Tam, N Rabinowitz, A Lampinen, NA Roy, S Chan, DJ Strouse, J Wang, ... Advances in neural information processing systems 35, 25377-25389, 2022 | 55 | 2022 |
| Improving the replicability of psychological science through pedagogy RXD Hawkins, EN Smith, C Au, JM Arias, R Catapano, E Hermann, M Keil, ... Advances in Methods and Practices in Psychological Science 1 (1), 7-18, 2018 | 53* | 2018 |
| Symbolic behaviour in artificial intelligence A Santoro, A Lampinen, K Mathewson, T Lillicrap, D Raposo arXiv preprint arXiv:2102.03406, 2021 | 43 | 2021 |
| Towards mental time travel: a hierarchical memory for reinforcement learning agents A Lampinen, S Chan, A Banino, F Hill Advances in Neural Information Processing Systems 34, 28182-28195, 2021 | 40 | 2021 |
| Tell me why! explanations support learning relational and causal structure AK Lampinen, N Roy, I Dasgupta, SCY Chan, A Tam, J Mcclelland, C Yan, ... International Conference on Machine Learning, 11868-11890, 2022 | 33 | 2022 |
| Symbol tuning improves in-context learning in language models J Wei, L Hou, A Lampinen, X Chen, D Huang, Y Tay, X Chen, Y Lu, ... arXiv preprint arXiv:2305.08298, 2023 | 27 | 2023 |
| Transformers generalize differently from information stored in context vs in weights SCY Chan, I Dasgupta, J Kim, D Kumaran, AK Lampinen, F Hill arXiv preprint arXiv:2210.05675, 2022 | 26 | 2022 |
| One-shot and few-shot learning of word embeddings AK Lampinen, JL McClelland arXiv preprint arXiv:1710.10280, 2017 | 25 | 2017 |
| Can language models handle recursively nested grammatical structures? A case study on comparing models and humans AK Lampinen arXiv preprint arXiv:2210.15303, 2022 | 20 | 2022 |
| Transforming task representations to perform novel tasks AK Lampinen, JL McClelland Proceedings of the National Academy of Sciences 117 (52), 32970-32981, 2020 | 19 | 2020 |
| Getting aligned on representational alignment I Sucholutsky, L Muttenthaler, A Weller, A Peng, A Bobu, B Kim, BC Love, ... arXiv preprint arXiv:2310.13018, 2023 | 18 | 2023 |
Felix HillResearch Scientist, DeepmindVerified email at google.com
