Hansen, Steven

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

Modelling the N400 brain potential as change in a probabilistic representation of meaning

Rabovsky, M., Hansen, S. S., & McClelland, J. L. (2018) · Nature Human Behaviour

Neurobiology of Language and BilingualismReading and Literacy Development

Cited by 290

In-context Reinforcement Learning with Algorithm Distillation

Laskin, M., Wang, L., Oh, J., Parisotto, E., Spencer, S., Steigerwald, R., Strouse, D., Hansen, S., Filos, A., Brooks, E., et al. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 14

Agency Is Frame-Dependent

Abel, D., Barreto, A., Bowling, M., Dabney, W., Dong, S., Hansen, S., Harutyunyan, A., Khetarpal, K., Lyle, C., Pascanu, R., et al. (2025) · arXiv

Philosophy of Biology and Scientific ExplanationEmbodied and Extended Cognition

Cited by 0