activity
20152026
most citedOvercoming catastrophic forgetting in neural networks

7.8k citations · 14k across the 38 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.CL2024★ 145 cited

Gemma 2: Improving Open Language Models at a Practical Size

Gemma Team, Morgane Riviere, Shreya Pathak +195

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In th…

q-bio.BM2024★ 60 cited

De novo design of high-affinity protein binders with AlphaProteo

Vinicius Zambaldi, David La, Alexander E. Chu +29

Computational design of protein-binding proteins is a fundamental capability with broad utility in biomedical research and biotechnology. Recent methods have made strides against s…

cs.AI2024★ 96 cited

Capabilities of Gemini Models in Medicine

Khaled Saab, Tao Tu, Wei-Hung Weng +64

Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date medical knowledge and understanding of…

cs.CL2024★ 238 cited

Gemma: Open Models Based on Gemini Research and Technology

Gemma Team, Thomas Mesnard, Cassidy Hardin +105

This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate stro…

cs.LG2024★ 4 cited

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Aleksandar Botev, Soham De, Samuel L Smith +59

We introduce RecurrentGemma, a family of open language models which uses Google's novel Griffin architecture. Griffin combines linear recurrences with local attention to achieve ex…