278 citations · 1.5k across the 50 of their papers we have counts for
9 papers · 1 filter
Future Querying: Can LLMs Serve as Implicit Medical World Models?
Siri Willems, James Butterworth, Lore Goetschalckx +4
Traditional clinical prediction models rely on task-specific pipelines and curated, structured data, which scale poorly and underutilize unstructured text. To address this, we intr…
Learning Dynamic Author Representations with Temporal Language Models
Edouard Delasalles, Sylvain Lamprier, Ludovic Denoyer
Language models are at the heart of numerous works, notably in the text mining and information retrieval communities. These statistical models aim at extracting word distributions,…
Large Memory Layers with Product Keys
Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato +2
This paper introduces a structured memory which can be easily integrated into a neural network. The memory is very large by design and significantly increases the capacity of the a…
Unsupervised Question Answering by Cloze Translation
Patrick Lewis, Ludovic Denoyer, Sebastian Riedel
Obtaining training data for Question Answering (QA) is time-consuming and resource-intensive, and existing QA datasets are only available for limited domains and languages. In this…
Multiple-Attribute Text Style Transfer
Sandeep Subramanian, Guillaume Lample, Eric Michael Smith +3
The dominant approach to unsupervised "style transfer" in text is based on the idea of learning a latent representation, which is independent of the attributes specifying its "styl…
A Reinforcement Learning-driven Translation Model for Search-Oriented Conversational Systems
Wafa Aissa, Laure Soulier, Ludovic Denoyer
Search-oriented conversational systems rely on information needs expressed in natural language (NL). We focus here on the understanding of NL expressions for building keyword-based…
Phrase-Based & Neural Unsupervised Machine Translation
Guillaume Lample, Myle Ott, Alexis Conneau +2
Machine translation systems achieve near human-level performance on some languages, yet their effectiveness strongly relies on the availability of large amounts of parallel sentenc…
Unsupervised Machine Translation Using Monolingual Corpora Only
Guillaume Lample, Alexis Conneau, Ludovic Denoyer +1
Machine translation has recently achieved impressive performance thanks to recent advances in deep learning and the availability of large-scale parallel corpora. There have been nu…
Word Translation Without Parallel Data
Alexis Conneau, Guillaume Lample, Marc'Aurelio Ranzato +2
State-of-the-art methods for learning cross-lingual word embeddings have relied on bilingual dictionaries or parallel corpora. Recent studies showed that the need for parallel data…