Ruoss, Anian

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

Language Modeling Is Compression

Delétang, G., Ruoss, A., Duquenne, P.-A., Catt, E., Genewein, T., Mattern, C., Grau-Moya, J., Wenliang, L. K., Aitchison, M., Orseau, L., et al. (2023) · arXiv

Topic ModelingAlgorithms and Data Compression

Cited by 39

Evaluating Frontier Models for Dangerous Capabilities

Phuong, M., Aitchison, M., Catt, E., Cogan, S., Kaskasoli, A., Krakovna, V., Lindner, D., Rahtz, M., Assael, Y., Hodkinson, S., et al. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 11

Randomized Positional Encodings Boost Length Generalization of Transformers

Ruoss, A., Delétang, G., Genewein, T., Grau-Moya, J., Csordás, R., Bennani, M., Legg, S., & Veness, J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations

Ruoss, A., Pardo, F., Chan, H., Li, B., Mnih, V., & Genewein, T. (2024) · arXiv

Reinforcement Learning in RoboticsMultimodal Machine Learning Applications

Cited by 0