Tacchetti, Andrea

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

Gemma: Open Models Based on Gemini Research and Technology

Gemma Team, Mesnard, T., Hardin, C., Dadashi, R., Bhupatiraju, S., Pathak, S., Sifre, L., Rivière, M., Kale, M. S., Love, J., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 284

Gemma 4 Technical Report

Gemma Team, Abd, S. E., Aggarwal, V., Algayres, R., Andreev, A., Bachem, O., Ballantyne, I., Brick, C., Cărbune, V., Casbon, M., et al. (2026) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 112

Unsupervised learning of invariant representations

Anselmi, F., Leibo, J. Z., Rosasco, L., Mutch, J., Tacchetti, A., & Poggio, T. (2016) · Theoretical Computer Science

Domain Adaptation and Few-Shot LearningAdvanced Image and Video Retrieval Techniques

Cited by 88

Human-centred mechanism design with Democratic AI

Koster, R., Balaguer, J., Tacchetti, A., Weinstein, A., Zhu, T., Hauser, O., Williams, D., Campbell-Gillingham, L., Thacker, P., Botvinick, M., et al. (2022) · Nature Human Behaviour

Game Theory and Voting SystemsEthics and Social Impacts of AI

Cited by 84

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

Scaffolding cooperation in human groups with deep reinforcement learning

McKee, K. R., Tacchetti, A., Bakker, M. A., Balaguer, J., Campbell-Gillingham, L., Everett, R., & Botvinick, M. (2023) · Nature Human Behaviour

Evolutionary Game Theory and CooperationExperimental Behavioral Economics Studies

Cited by 43

Deep reinforcement learning can promote sustainable human behaviour in a common-pool resource problem

Koster, R., Pîslar, M., Tacchetti, A., Balaguer, J., Liu, L., Elie, R., Hauser, O. P., Tuyls, K., Botvinick, M., & Summerfield, C. (2025) · Nature Communications

Experimental Behavioral Economics StudiesEvolutionary Game Theory and Cooperation

Cited by 12

The Good Shepherd: An Oracle Agent for Mechanism Design

Balaguer, J., Koster, R., Summerfield, C., & Tacchetti, A. (2022) · arXiv

Game Theory and ApplicationsAuction Theory and Applications

Cited by 4