Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task

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

Devis Tuia, Christel Marie Tartini-Chappuis, Sylvain Lobry, 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 ...

2022

How We Use Wikipedia: Studying Readers' Behavior with Navigation Traces

Tiziano Piccardi

In the information age, the Web and the growing global connectivity drastically simplified our access to information. Learning and fact-checking from online resources is nowadays part of our daily routine. Studying the dynamic associated with online conten ...

EPFL2022

Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling

Vinitra Swamy, Tanja Christina Käser Jacober, Thiemo Wambsganss

Natural Language Processing (NLP) has become increasingly utilized to provide adaptivity in educational applications. However, recent research has highlighted a variety of biases in pre-trained language models. While existing studies investigate bias in di ...

2022

Strong Heuristics for Named Entity Linking

Robert West, Akhil Arora, Andreas Oliver Spitz, Marko Culjak

Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods. However, such methods tend to come with caveats, such as no integration of ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

Unsupervised Term Extraction for Highly Technical Domains

Diego Matteo Antognini

Term extraction is an information extraction task at the root of knowledge discovery platforms. Developing term extractors that are able to generalize across very diverse and potentially highly technical domains is challenging, as annotations for domains r ...

2022

Learning computationally efficient static word and sentence representations

Prakhar Gupta

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 ...

EPFL2021

Further results on latent discourse models and word embeddings

Youssef Allouah

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 Publishing2021

Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications

Petr Motlicek, Amrutha Prasad

Voice communication is the main channel to exchange information between pilots and Air-Traffic Controllers (ATCos). Recently, several projects have explored the employment of speech recognition technology to automatically extract spoken key information suc ...

MDPI2021

Lightweight Cross-Lingual Sentence Representation Learning

Martin Jaggi, Prakhar Gupta, Zhuoyuan Mao

Large-scale models for learning fixed-dimensional cross-lingual sentence representations like LASER (Artetxe and Schwenk, 2019b) lead to significant improvement in performance on downstream tasks. However, further increases and modifications based on such ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

RSVQA Meets Bigearthnet: A New, Large-Scale, Visual Question Answering Dataset for Remote Sensing

Devis Tuia, Sylvain Lobry

Visual Question Answering is a new task that can facilitate the extraction of information from images through textual queries: it aims at answering an open-ended question formulated in natural language about a given image. In this work, we introduce a new ...

IEEE2021

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