Buthpitiya, Senaka

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

Activity-Aware Mental Stress Detection Using Physiological Sensors

Sun, F.-T., Kuo, C., Cheng, H.-T., Buthpitiya, S., Collins, P., & Griss, M. (2012) · Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Emotion and Mood RecognitionContext-Aware Activity Recognition Systems

Cited by 292

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

Stretching Sentence-pair NLI Models to Reason over Long Documents and Clusters

Schuster, T., Chen, S., Buthpitiya, S., Fabrikant, A., & Metzler, D. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Topic ModelingNatural Language Processing Techniques

Cited by 17