2.7k citations · 3.9k across the 8 of their papers we have counts for
9 papers · 1 filter
Code Llama: Open Foundation Models for Code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle +23
We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for lar…
Llama 2: Open Foundation and Fine-Tuned Chat Models
Hugo Touvron, Louis Martin, Kevin Stone +65
In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our f…
Efficient Large Scale Language Modeling with Mixtures of Experts
Mikel Artetxe, Shruti Bhosale, Naman Goyal +21
Mixture of Experts layers (MoEs) enable efficient scaling of language models through conditional computation. This paper presents a detailed empirical study of how autoregressive M…
ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations
Fernando Alva-Manchego, Louis Martin, Antoine Bordes +3
In order to simplify a sentence, human editors perform multiple rewriting transformations: they split it into several shorter sentences, paraphrase words (i.e. replacing complex wo…
MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases
Louis Martin, Angela Fan, Éric de la Clergerie +2
Progress in sentence simplification has been hindered by a lack of labeled parallel simplification data, particularly in languages other than English. We introduce MUSS, a Multilin…
CamemBERT: a Tasty French Language Model
Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez +5
Pretrained language models are now ubiquitous in Natural Language Processing. Despite their success, most available models have either been trained on English data or on the concat…
Controllable Sentence Simplification
Louis Martin, Benoît Sagot, Éric de la Clergerie +1
Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical. It is often conside…
EASSE: Easier Automatic Sentence Simplification Evaluation
Fernando Alva-Manchego, Louis Martin, Carolina Scarton +1
We introduce EASSE, a Python package aiming to facilitate and standardise automatic evaluation and comparison of Sentence Simplification (SS) systems. EASSE provides a single acces…
Reference-less Quality Estimation of Text Simplification Systems
Louis Martin, Samuel Humeau, Pierre-Emmanuel Mazaré +3
The evaluation of text simplification (TS) systems remains an open challenge. As the task has common points with machine translation (MT), TS is often evaluated using MT metrics su…