| 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 | 739 | 2022 |
| 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 | 683 | 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 | 590* | 2021 |
| 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 | 584 | 2022 |
| 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 | 238 | 2014 |
| Understanding the Capabilities A Tamkin, M Brundage, J Clark, D Ganguli Limitations, and Societal Impact of Large Language Models, 2021 | 235* | 2021 |
| Efficient sensory encoding and Bayesian inference with heterogeneous neural populations D Ganguli, EP Simoncelli Neural computation 26 (10), 2103-2134, 2014 | 228 | 2014 |
| 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 | 223 | 2022 |
| 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 | 214 | 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 | 214 | 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 | 189 | 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 | 172 | 2022 |
| 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, 2021 | 167* | 2021 |
| 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 | 125 | 2022 |
| Implicit encoding of prior probabilities in optimal neural populations D Ganguli, E Simoncelli Advances in neural information processing systems 23, 2010 | 106 | 2010 |
| 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 | 93 | 2023 |
| Towards measuring the representation of subjective global opinions in language models E Durmus, K Nyugen, TI Liao, N Schiefer, A Askell, A Bakhtin, C Chen, ... arXiv preprint arXiv:2306.16388, 2023 | 62 | 2023 |
| Neural and perceptual signatures of efficient sensory coding D Ganguli, EP Simoncelli arXiv preprint arXiv:1603.00058, 2016 | 26 | 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 | 23* | 2018 |
| Evaluating and mitigating discrimination in language model decisions A Tamkin, A Askell, L Lovitt, E Durmus, N Joseph, S Kravec, K Nguyen, ... arXiv preprint arXiv:2312.03689, 2023 | 11 | 2023 |
