activity
20182024
most citedUnsupervised Open Relation Extraction

22 citations · 75 across the 10 of their papers we have counts for

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Showing cs.CLShow all

13 papers · 1 filter

cs.CL202410 cited

Large Concept Models: Language Modeling in a Sentence Representation Space

LCM team, Loïc Barrault, Paul-Ambroise Duquenne +18

LLMs have revolutionized the field of artificial intelligence and have emerged as the de-facto tool for many tasks. The current established technology of LLMs is to process input a…

cs.CL2023

Seamless: Multilingual Expressive and Streaming Speech Translation

Seamless Communication, Loïc Barrault, Yu-An Chung +62

Large-scale automatic speech translation systems today lack key features that help machine-mediated communication feel seamless when compared to human-to-human dialogue. In this wo…

cs.CL202314 cited

SeamlessM4T: Massively Multilingual & Multimodal Machine Translation

Seamless Communication, Loïc Barrault, Yu-An Chung +65

What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed…

cs.CL20226 cited

What Language Model to Train if You Have One Million GPU Hours?

Teven Le Scao, Thomas Wang, Daniel Hesslow +16

The crystallization of modeling methods around the Transformer architecture has been a boon for practitioners. Simple, well-motivated architectural variations can transfer across t…

cs.CL20222 cited

Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources

Angelina McMillan-Major, Zaid Alyafeai, Stella Biderman +15

In recent years, large-scale data collection efforts have prioritized the amount of data collected in order to improve the modeling capabilities of large language models. This prio…

cs.CL20218 cited

Unsupervised and Distributional Detection of Machine-Generated Text

Matthias Gallé, Jos Rozen, Germán Kruszewski +1

The power of natural language generation models has provoked a flurry of interest in automatic methods to detect if a piece of text is human or machine-authored. The problem so far…