Strouse, DJ

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

OpenAI GPT-5 System Card

Singh, A., Fry, A., Perelman, A., Tart, A., Ganesh, A., El-Kishky, A., McLaughlin, A., Low, A., Ostrow, A., Ananthram, A., et al. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 26

Semantic Exploration from Language Abstractions and Pretrained Representations

Tam, A. C., Rabinowitz, N. C., Lampinen, A. K., Roy, N. A., Chan, S. C. Y., Strouse, D., Wang, J. X., Banino, A., & Hill, F. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 24

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

Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs

Singh, A. K., & Strouse, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 11

Melting Pot 2.0

Agapiou, J. P., Vezhnevets, A. S., Duéñez-Guzmán, E. A., Matyas, J., Mao, Y., Sunehag, P., Köster, R., Madhushani, U., Kopparapu, K., Comanescu, R., et al. (2022) · arXiv

Multi-Agent Systems and NegotiationReinforcement Learning in Robotics

Cited by 3