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20132025
most citedDistilling the Knowledge in a Neural Network

14.1k citations · 17.1k across the 31 of their papers we have counts for

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10 papers · 1 filter

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…

cs.CL2024238 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.CL202223 cited

Unified Scaling Laws for Routed Language Models

Aidan Clark, Diego de las Casas, Aurelia Guy +23

The performance of a language model has been shown to be effectively modeled as a power-law in its parameter count. Here we study the scaling behaviors of Routing Networks: archite…

cs.CL2022243 cited

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Jack W. Rae, Sebastian Borgeaud, Trevor Cai +77

Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.…

cs.CL20214 cited

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset

Luyu Wang, Yujia Li, Ozlem Aslan +1

We present a new dataset of Wikipedia articles each paired with a knowledge graph, to facilitate the research in conditional text generation, graph generation and graph representat…