Firoiu, Vlad

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

Improving alignment of dialogue agents via targeted human judgements

Glaese, A., McAleese, N., Trębacz, M., Aslanides, J., Firoiu, V., Ewalds, T., Rauh, M., Weidinger, L., Chadwick, M., Thacker, P., et al. (2022) · arXiv

Speech and dialogue systemsIntelligent Tutoring Systems and Adaptive Learning

Cited by 134

At Human Speed: Deep Reinforcement Learning with Action Delay

Firoiu, V., Ju, T., & Tenenbaum, J. (2018) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 29

Training a First-Order Theorem Prover from Synthetic Data

Firoiu, V., Aygun, E., Anand, A., Ahmed, Z., Glorot, X., Orseau, L., Zhang, L., Precup, D., & Mourad, S. (2021) · arXiv

Logic, programming, and type systemsLogic, Reasoning, and Knowledge

Cited by 15