Concept
Sentence embedding
Publications associées (23)
Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework
This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine ...
ASSOC COMPUTING MACHINERY2023Text Representation Learning for Low Cost Natural Language Understanding
Jan Frederik Jonas Florian Mai
Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...
EPFL2023Prompt–RSVQA: Prompting visual context to a language model for Remote Sensing Visual Question Answering
Devis Tuia, Sylvain Lobry, Christel Marie Tartini-Chappuis, Valérie Zermatten
Remote sensing visual question answering (RQA) was recently proposed with the aim of interfacing natural language and vision to ease the access of information contained in Earth Observation data for a wide audience, which is granted by simple questions in ...
2022Learning computationally efficient static word and sentence representations
Most of the Natural Language Processing (NLP) algorithms involve use of distributed vector representations of linguistic units (primarily words and sentences) also known as embeddings in one way or another. These embeddings come in two flavours namely, sta ...
EPFL2021Further results on latent discourse models and word embeddings
We discuss some properties of generative models for word embeddings. Namely, (Arora et al., 2016) proposed a latent discourse model implying the concentration of the partition function of the word vectors. This concentration phenomenon led to an asymptotic ...
MICROTOME PUBL2021