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Cem Anil
Cem Anil
University of Toronto; Vector Institute
Verified email at mail.utoronto.ca
Title
Cited by
Cited by
Year
Training deep networks with synthetic data: Bridging the reality gap by domain randomization
J Tremblay, A Prakash, D Acuna, M Brophy, V Jampani, C Anil, T To, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
10852018
Solving quantitative reasoning problems with language models
A Lewkowycz, A Andreassen, D Dohan, E Dyer, H Michalewski, ...
Advances in Neural Information Processing Systems 35, 3843-3857, 2022
6002022
Sorting out lipschitz function approximation
C Anil, J Lucas, R Grosse
International Conference on Machine Learning, 291-301, 2019
3782019
Towards monosemanticity: Decomposing language models with dictionary learning
T Bricken, A Templeton, J Batson, B Chen, A Jermyn, T Conerly, N Turner, ...
Transformer Circuits Thread 2, 2023
2342023
Exploring length generalization in large language models
C Anil, Y Wu, A Andreassen, A Lewkowycz, V Misra, V Ramasesh, ...
Advances in Neural Information Processing Systems 35, 38546-38556, 2022
1822022
Timbretron: A wavenet (cyclegan (cqt (audio))) pipeline for musical timbre transfer
S Huang, Q Li, C Anil, X Bao, S Oore, RB Grosse
arXiv preprint arXiv:1811.09620, 2018
1402018
Studying large language model generalization with influence functions
R Grosse, J Bae, C Anil, N Elhage, A Tamkin, A Tajdini, B Steiner, D Li, ...
arXiv preprint arXiv:2308.03296, 2023
1132023
Preventing gradient attenuation in lipschitz constrained convolutional networks
Q Li, S Haque, C Anil, J Lucas, RB Grosse, JH Jacobsen
Advances in neural information processing systems 32, 2019
1122019
Many-shot jailbreaking
C Anil, E Durmus, M Sharma, J Benton, S Kundu, J Batson, N Rimsky, ...
Anthropic, April, 2024
652024
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
522024
Solving quantitative reasoning problems with language models, 2022
A Lewkowycz, A Andreassen, D Dohan, E Dyer, H Michalewski, ...
URL https://arxiv. org/abs/2206.14858, 2022
422022
Generation of synthetic images for training a neural network model
J Tremblay, A Prakash, MA Brophy, V Jampani, C Anil, ST Birchfield, ...
US Patent 10,867,214, 2020
232020
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
C Anil, A Pokle, K Liang, J Treutlein, Y Wu, S Bai, JZ Kolter, RB Grosse
Advances in Neural Information Processing Systems 35, 7796-7809, 2022
192022
Learning to Give Checkable Answers with Prover-Verifier Games
C Anil, G Zhang, Y Wu, R Grosse
arXiv preprint arXiv:2108.12099, 2021
122021
Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data
J Treutlein, D Choi, J Betley, C Anil, S Marks, RB Grosse, O Evans
arXiv preprint arXiv:2406.14546, 2024
82024
Learning to Elect
C Anil, X Bao
Advances in Neural Information Processing Systems 34, 8006-8017, 2021
82021
Refining labeling of time-associated data
C Anil
US Patent App. 16/153,430, 2019
82019
Out-of-Distribution Generalization with Deep Equilibrium Models
K Liang, C Anil, Y Wu, R Grosse
ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning, 2021
62021
Sabotage Evaluations for Frontier Models
J Benton, M Wagner, E Christiansen, C Anil, E Perez, J Srivastav, ...
arXiv preprint arXiv:2410.21514, 2024
2024
Neural network model trained using generated synthetic images
J Tremblay, A Prakash, MA Brophy, V Jampani, C Anil, ST Birchfield, ...
US Patent 11,715,251, 2023
2023
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