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Prompt–RSVQA: Prompting visual context to a language model for Remote Sensing Visual Question Answering

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Deep Learning Works in Practice. But Does it Work in Theory?

Rachid Guerraoui, Le Nguyen Hoang

Deep learning relies on a very specific kind of neural networks: those superposing several neural layers. In the last few years, deep learning achieved major breakthroughs in many tasks such as image analysis, speech recognition, natural language processin ...

2018

Learning Word Vectors for 157 Languages

Prakhar Gupta, Edouard Grave

Distributed word representations, or word vectors, have recently been applied to many tasks in natural language processing, leading to state-of-the-art performance. A key ingredient to the successful application of these representations is to train them on ...

2018

How grouping determines crowding

Michael Herzog

Crowding is traditionally thought to occur by local interactions between the target and the neighboring flankers, for example, by pooling neural responses corresponding to both the target and flankers. Accordingly, crowding is thought to occur within a sma ...

2017

Word Sequence Modeling using Deep Learning

Joël Yvon Roland Legrand

For a long time, natural language processing (NLP) has relied on generative models with task specific and manually engineered features. Recently, there has been a resurgence of interest for neural networks in the machine learning community, obtaining state ...

EPFL2016

Building Word Embeddings for Solving Natural Language Processing

Rémi Philippe Lebret

Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

École Polytechnique Fédérale de Lausanne2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

EPFL2016

Twitter Sentiment Analysis (Almost) from Scratch

Rémi Philippe Lebret, Ronan Collobert, Pedro Henrique Oliveira Pinheiro

A popular application in Natural Language Processing (NLP) is the Sentiment Analysis (SA), i.e., the task of extracting contextual polarity from a given text. The social network Twitter provides an immense amount of text (called tweets) generated by users ...

Idiap2016

The Honeycomb illusion: Uniform textures not perceived as such

Michael Herzog

We present a series of patterns, in which texture is perceived differently at fixation in comparison to the periphery, such that a physically uniform stimulus yields a nonuniform percept. We call this the Honeycomb illusion, and we discuss it in relation t ...

2016

Simple Image Description Generator via a Linear Phrase-based Model

Rémi Philippe Lebret, Ronan Collobert, Pedro Henrique Oliveira Pinheiro

Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model that is able to generate descriptive sentences given a sample image. This m ...

Idiap2015

Phrase-based Image Captioning

Rémi Philippe Lebret, Ronan Collobert, Pedro Henrique Oliveira Pinheiro

2015