| Training a helpful and harmless assistant with reinforcement learning from human feedback Y Bai, A Jones, K Ndousse, A Askell, A Chen, N DasSarma, D Drain, ... arXiv preprint arXiv:2204.05862, 2022 | 934 | 2022 |
| 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 | 859 | 2022 |
| Constitutional ai: Harmlessness from ai feedback Y Bai, S Kadavath, S Kundu, A Askell, J Kernion, A Jones, A Chen, ... arXiv preprint arXiv:2212.08073, 2022 | 746 | 2022 |
| The AI index 2021 annual report D Zhang, S Mishra, E Brynjolfsson, J Etchemendy, D Ganguli, B Grosz, ... arXiv preprint arXiv:2103.06312, 2021 | 600 | 2021 |
| Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned D Ganguli, L Lovitt, J Kernion, A Askell, Y Bai, S Kadavath, B Mann, ... arXiv preprint arXiv:2209.07858, 2022 | 289 | 2022 |
| A general language assistant as a laboratory for alignment A Askell, Y Bai, A Chen, D Drain, D Ganguli, T Henighan, A Jones, ... arXiv preprint arXiv:2112.00861, 2021 | 276 | 2021 |
| Understanding the Capabilities Limitations, and Societal Impact of Large Language Models A Tamkin, M Brundage, J Clark, D Ganguli arXiv preprint arxiv:2102.02503, 2021 | 261 | 2021 |
| Druid: A real-time analytical data store F Yang, E Tschetter, X Léauté, N Ray, G Merlino, D Ganguli Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014 | 236 | 2014 |
| Efficient sensory encoding and Bayesian inference with heterogeneous neural populations D Ganguli, EP Simoncelli Neural computation 26 (10), 2103-2134, 2014 | 235 | 2014 |
| A mathematical framework for transformer circuits N Elhage, N Nanda, C Olsson, T Henighan, N Joseph, B Mann, A Askell, ... Transformer Circuits Thread 1 (1), 12, 2021 | 228* | 2021 |
| In-context learning and induction heads C Olsson, N Elhage, N Nanda, N Joseph, N DasSarma, T Henighan, ... arXiv preprint arXiv:2209.11895, 2022 | 225 | 2022 |
| Predictability and surprise in large generative models D Ganguli, D Hernandez, L Lovitt, A Askell, Y Bai, A Chen, T Conerly, ... Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 219 | 2022 |
| Discovering language model behaviors with model-written evaluations E Perez, S Ringer, K Lukošiūtė, K Nguyen, E Chen, S Heiner, C Pettit, ... arXiv preprint arXiv:2212.09251, 2022 | 161 | 2022 |
| The capacity for moral self-correction in large language models D Ganguli, A Askell, N Schiefer, TI Liao, K Lukošiūtė, A Chen, A Goldie, ... arXiv preprint arXiv:2302.07459, 2023 | 112 | 2023 |
| Implicit encoding of prior probabilities in optimal neural populations D Ganguli, E Simoncelli Advances in neural information processing systems 23, 2010 | 109 | 2010 |
| Language models (mostly) know what they know S Kadavath, T Conerly, A Askell, T Henighan, D Drain, E Perez, ... arXiv preprint arXiv:2207.05221, 2022 | 103 | 2022 |
| Towards measuring the representation of subjective global opinions in language models E Durmus, K Nguyen, TI Liao, N Schiefer, A Askell, A Bakhtin, C Chen, ... arXiv preprint arXiv:2306.16388, 2023 | 94 | 2023 |
| Neural and perceptual signatures of efficient sensory coding D Ganguli, EP Simoncelli arXiv preprint arXiv:1603.00058, 2016 | 28 | 2016 |
| Starfish: Open source image based transcriptomics and proteomics tools S Axelrod, AJ Carr, J Freeman, D Ganguli, B Long, T Tung J. Open Source Softw 6, 2440, 2018 | 27* | 2018 |
| Sleeper agents: Training deceptive llms that persist through safety training E Hubinger, C Denison, J Mu, M Lambert, M Tong, M MacDiarmid, ... arXiv preprint arXiv:2401.05566, 2024 | 24 | 2024 |
