activity
20222026
most citedGemma 3 Technical Report

65 citations · 173 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

DiffusionGemma Technical Report

DiffusionGemma Team, Adrien Ali Taïga, James Assiene +41

We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rather than decoding one token at…

cs.CL2026★ 3 cited

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…

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★ 2 cited

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.AI2025★ 41 cited

MedGemma Technical Report

Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri +78

Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks,…

cs.CL2025★ 65 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.LG2023★ 56 cited

Zephyr: Direct Distillation of LM Alignment

Lewis Tunstall, Edward Beeching, Nathan Lambert +11

We aim to produce a smaller language model that is aligned to user intent. Previous research has shown that applying distilled supervised fine-tuning (dSFT) on larger models signif…

cs.CL2023★ 1 cited

AfroDigits: A Community-Driven Spoken Digit Dataset for African Languages

Chris Chinenye Emezue, Sanchit Gandhi, Lewis Tunstall +10

The advancement of speech technologies has been remarkable, yet its integration with African languages remains limited due to the scarcity of African speech corpora. To address thi…

cs.CL2022

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

BigScience Workshop, :, Teven Le Scao +391

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…

cs.LG2022★ 5 cited

Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements

Leandro von Werra, Lewis Tunstall, Abhishek Thakur +16

Evaluation is a key part of machine learning (ML), yet there is a lack of support and tooling to enable its informed and systematic practice. We introduce Evaluate and Evaluation o…