Welty, Chris

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 2: Improving Open Language Models at a Practical Size

Gemma Team, Riviere, M., Pathak, S., Sessa, P. G., Hardin, C., Bhupatiraju, S., Hussenot, L., Mesnard, T., Shahriari, B., Ramé, A., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 149

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

Crowdsourcing Ground Truth for Medical Relation Extraction

Dumitrache, A., Aroyo, L., & Welty, C. (2018) · ACM Transactions on Interactive Intelligent Systems

Biomedical Text Mining and OntologiesMobile Crowdsensing and Crowdsourcing

Cited by 60

The Three Sides of CrowdTruth

Aroyo, L., & Welty, C. (2014) · Human Computation

Mobile Crowdsensing and CrowdsourcingSpam and Phishing Detection

Cited by 43

Introducing v0.5 of the AI Safety Benchmark from MLCommons

Vidgen, B., Agrawal, A., Ahmed, A. M., Akinwande, V., Al-Nuaimi, N., Alfaraj, N., Alhajjar, E., Aroyo, L., Bavalatti, T., Bartolo, M., et al. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 5