activity
20242026
most citedGemma 2: Improving Open Language Models at a Practical Size

145 citations · 212 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL20262 cited

TranslateGemma Technical Report

Mara Finkelstein, Isaac Caswell, Tobias Domhan +18

We present TranslateGemma, a suite of open machine translation models based on the Gemma 3 foundation models. To enhance the inherent multilingual capabilities of Gemma 3 for the t…

cs.CL2025

T5Gemma 2: Seeing, Reading, and Understanding Longer

Biao Zhang, Paul Suganthan, Gaël Liu +17

We introduce T5Gemma 2, the next generation of the T5Gemma family of lightweight open encoder-decoder models, featuring strong multilingual, multimodal and long-context capabilitie…

cs.CL2025

EmbeddingGemma: Powerful and Lightweight Text Representations

Henrique Schechter Vera, Sahil Dua, Biao Zhang +86

We introduce EmbeddingGemma, a new lightweight, open text embedding model based on the Gemma 3 language model family. Our innovative training recipe strategically captures knowledg…

cs.LG2025

Assay2Mol: large language model-based drug design using BioAssay context

Yifan Deng, Spencer S. Ericksen, Anthony Gitter

Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…

cs.CL202565 cited

Gemma 3 Technical Report

Gemma Team, Aishwarya Kamath, Johan Ferret +209

We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. This version introduces vision underst…

cs.CL2024145 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…