Parisi, Aaron

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 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

TALM: Tool Augmented Language Models

Parisi, A., Zhao, Y., & Fiedel, N. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 35

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Singh, A., Co-Reyes, J. D., Agarwal, R., Anand, A., Patil, P., Garcia, X., Liu, P. J., Harrison, J., Lee, J., Xu, K., et al. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

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Enhancing LLM Planning Capabilities through Intrinsic Self-Critique

Bohnet, B., Kamienny, P.-A., Sedghi, H., Gorur, D., Awasthi, P., Parisi, A., Swersky, K., Liu, R., Nova, A., & Fiedel, N. (2025) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence in Games

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