Huot, Fantine

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

Scaling vision transformers to 22 billion parameters

Dehghani, M., Djolonga, J., Mustafa, B., Padlewski, P., Heek, J., Gilmer, J., Steiner, A., Caron, M., Geirhos, R., Alabdulmohsin, I., et al. (2023) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 112

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Conditional Generation with a Question-Answering Blueprint

Narayan, S., Maynez, J., Amplayo, R. K., Ganchev, K., Louis, A., Huot, F., Sandholm, A., Das, D., & Lapata, M. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 24

Learning to Plan and Generate Text with Citations

Fierro, C., Amplayo, R. K., Huot, F., De Cao, N., Maynez, J., Narayan, S., & Lapata, M. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12