| Relational inductive biases, deep learning, and graph networks PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 3410 | 2018 |
| Scaling language models: Methods, analysis & insights from training gopher JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ... arXiv preprint arXiv:2112.11446, 2021 | 743 | 2021 |
| Machine theory of mind N Rabinowitz, F Perbet, F Song, C Zhang, SMA Eslami, M Botvinick International conference on machine learning, 4218-4227, 2018 | 547 | 2018 |
| Task representations in neural networks trained to perform many cognitive tasks GR Yang, MR Joglekar, HF Song, WT Newsome, XJ Wang Nature neuroscience 22 (2), 297-306, 2019 | 457 | 2019 |
| The hanabi challenge: A new frontier for ai research N Bard, JN Foerster, S Chandar, N Burch, M Lanctot, HF Song, E Parisotto, ... Artificial Intelligence 280, 103216, 2020 | 371 | 2020 |
| Stabilizing transformers for reinforcement learning E Parisotto, F Song, J Rae, R Pascanu, C Gulcehre, S Jayakumar, ... International conference on machine learning, 7487-7498, 2020 | 339 | 2020 |
| Red teaming language models with language models E Perez, S Huang, F Song, T Cai, R Ring, J Aslanides, A Glaese, ... arXiv preprint arXiv:2202.03286, 2022 | 296 | 2022 |
| Bipartite fluctuations as a probe of many-body entanglement HF Song, S Rachel, C Flindt, I Klich, N Laflorencie, K Le Hur Physical Review B 85 (3), 035409, 2012 | 296 | 2012 |
| Training excitatory-inhibitory recurrent neural networks for cognitive tasks: a simple and flexible framework HF Song, GR Yang, XJ Wang PLoS computational biology 12 (2), e1004792, 2016 | 254 | 2016 |
| Circuit mechanisms for the maintenance and manipulation of information in working memory NY Masse, GR Yang, HF Song, XJ Wang, DJ Freedman Nature neuroscience 22 (7), 1159-1167, 2019 | 187 | 2019 |
| Relational inductive biases, deep learning, and graph networks. arXiv 2018 PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 171 | 2018 |
| Bayesian action decoder for deep multi-agent reinforcement learning J Foerster, F Song, E Hughes, N Burch, I Dunning, S Whiteson, ... International Conference on Machine Learning, 1942-1951, 2019 | 164 | 2019 |
| General relation between entanglement and fluctuations in one dimension HF Song, S Rachel, K Le Hur Physical Review B 82 (1), 012405, 2010 | 157 | 2010 |
| Reward-based training of recurrent neural networks for cognitive and value-based tasks HF Song, GR Yang, XJ Wang Elife 6, e21492, 2017 | 154 | 2017 |
| Entanglement entropy from charge statistics: Exact relations for noninteracting many-body systems HF Song, C Flindt, S Rachel, I Klich, K Le Hur Physical Review B 83 (16), 161408, 2011 | 146 | 2011 |
| Teaching language models to support answers with verified quotes J Menick, M Trebacz, V Mikulik, J Aslanides, F Song, M Chadwick, ... arXiv preprint arXiv:2203.11147, 2022 | 136 | 2022 |
| V-mpo: On-policy maximum a posteriori policy optimization for discrete and continuous control HF Song, A Abdolmaleki, JT Springenberg, A Clark, H Soyer, JW Rae, ... arXiv preprint arXiv:1909.12238, 2019 | 103 | 2019 |
| Detecting quantum critical points using bipartite fluctuations S Rachel, N Laflorencie, HF Song, K Le Hur Physical review letters 108 (11), 116401, 2012 | 103 | 2012 |
| Entanglement entropy of the two-dimensional Heisenberg antiferromagnet HF Song, N Laflorencie, S Rachel, K Le Hur Physical Review B 83 (22), 224410, 2011 | 103 | 2011 |
| From motor control to team play in simulated humanoid football S Liu, G Lever, Z Wang, J Merel, SMA Eslami, D Hennes, WM Czarnecki, ... Science Robotics 7 (69), eabo0235, 2022 | 101 | 2022 |
