Publications related to The SUMMA Platform Prototype

Dense Image-based Predictions for Comics Analysis

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

EPFL2023

impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers

Maud Ehrmann, Matteo Romanello

Text Reuse reveals meaningful reiterations of text in large corpora. Humanities researchers use text reuse to study, e.g., the posterior reception of influential texts or to reveal evolving publication practices of historical media. This research is often ...

2023

Improved framework to estimate travel time and derived distributions in hydrological control volumes

Mitra Asadollahi

Crossing properties of soil saturation, defined as the duration and excursion of soil saturation below and above certain thresholds, are key variables to ecosystem functioning and evolution by primarily influencing the plant and soil microbes physiological ...

EPFL2022

Discourse Phenomena in Machine Translation

Lesly Sadiht Miculicich Werlen

Machine Translation (MT) has made considerable progress in the past two decades, particularly after the introduction of neural network models (NMT). During this time, the research community has mostly focused on modeling and evaluating MT systems at the se ...

EPFL2021

Subword Mapping and Anchoring across Languages

Andrei Popescu-Belis

State-of-the-art multilingual systems rely on shared vocabularies that sufficiently cover all considered languages. To this end, a simple and frequently used approach makes use of subword vocabularies constructed jointly over several languages. We hypothes ...

Assoc Computational Linguistics-Acl2021

Loss landscape and symmetries in Neural Networks

Mario Geiger

Neural networks (NNs) have been very successful in a variety of tasks ranging from machine translation to image classification. Despite their success, the reasons for their performance are still not well-understood. This thesis explores two main themes: lo ...

EPFL2021

Epidemic mitigation by statistical inference from contact tracing data

Maria Refinetti, Giovanni Catania, Florent Gérard Krzakala, Lenka Zdeborová, Indaco Biazzo

Contact tracing is an essential tool to mitigate the impact of a pandemic, such as the COVID-19 pandemic. In order to achieve efficient and scalable contact tracing in real time, digital devices can play an important role. While a lot of attention has been ...

National Academy of Sciences2021

Classifying Dyads for Militarized Conflict Analysis

Robert West

Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationships between entity pairs (dyadic causes) and multi-lateral relationships amon ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation

Petr Motlicek

The preparation of parallel corpora is a challenging task, particularly for languages that suffer from under-representation in the digital world. In a multi-lingual country like India, the need for such parallel corpora is stringent for several low-resourc ...

European Language Resources Association (ELRA)2020

An effective rule for translating optimal selective laser melting processing parameters from one material to another

Eric Boillat, Jamasp Jhabvala, Rita Drissi Daoudi, Roland Logé, Hossein Ghasemi Tabasi, Toni Ivas

Selective Laser Melting (SLM) or Laser Powder Bed Fusion (L-PBF) is the most studied laser-based additive manufacturing process for metals and alloys. One important issue in SLM is the time-consuming identification of a process window leading to quasi full ...

2020

Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement

James Henderson, Alireza Mohammadshahi

We propose the Recursive Non-autoregressive Graph-to-graph Transformer architecture (RNG-Tr) for the iterative refinement of arbitrary graphs through the recursive application of a non-autoregressive Graph-to-Graph Transformer and apply it to syntactic dep ...

2021

Transfer Learning from Pre-trained BERT for Pronoun Resolution

Xingce Bao, Qianqian Qiao

The paper describes the submission of the team "We used bert!" to the shared task Gendered Pronoun Resolution (Pair pronouns to their correct entities). Our final submission model based on the fine-tuned BERT (Bidirectional Encoder Representations from Tra ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2019

Word Sense Consistency in Statistical and Neural Machine Translation

Xiao Pu

Different senses of source words must often be rendered by different words in the target language when performing machine translation (MT). Selecting the correct translation of polysemous words can be done based on the contexts of use. However, state-of-th ...

EPFL2018

Intonation Modelling for Speech Synthesis and Emphasis Preservation

Pierre-Edouard Jean Charles Honnet

Speech-to-speech translation is a framework which recognises speech in an input language, translates it to a target language and synthesises speech in this target language. In such a system, variations in the speech signal which are inherent to natural hum ...

EPFL2017

Matrix-binding checkpoint immunotherapies enhance antitumor efficacy and reduce adverse events

Jeffrey Alan Hubbell, Melody Swartz, Lambert Charles François Potin, Hans Mattias Larsson, Gabriele Galliverti, Jun Ishihara, Kazuto Fukunaga

Immune checkpoint blockade exhibits considerable antitumor activity, but previous studies have reported instances of severe treatment-related adverse events. We sought to explore local immune checkpoint blockade, with an antibody (Ab) form that would be re ...

Amer Assoc Advancement Science2017

LMS-Verify: Abstraction without Regret for Verified Systems Programming’

Nada Amin, Tiark Rompf

Performance critical software is almost always developed in C, as programmers do not trust high-level languages to deliver the same reliable performance. This is bad because low-level code in unsafe languages attracts security vulnerabilities and because d ...

Assoc Computing Machinery2017

Cross-lingual Linking of Multi-word Entities and their corresponding Acronyms

Maud Ehrmann

This paper reports on an approach and experiments to automatically build a cross-lingual multi-word entity resource. Starting from a collection of millions of acronym/expansion pairs for 22 languages where expansion variants were grouped into monolingual c ...

European Language Resources Association (ELRA)2016

Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury

Léonie Asboth, Jérôme Gandar, Stéphanie Lacour, Arthur Edouard Hirsch, Silvestro Micera, Grégoire Courtine, Nikolaus Wenger, Ivan Rusev Minev, Rubia van den Brand, Quentin Barraud, Simone Ellen Joze Duis, Eduardo Martin Moraud, Pavel Musienko, Marco Capogrosso, Natalia Pavlova, Julie Kreider, Laetitia Danielle Philippine Baud, Andrea Mortera, Jocelyne Bloch

Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited the ther ...

Nature Publishing Group2016

Word Sequence Modeling using Deep Learning : an End-to-end Approach and its Applications

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

Discourse-level features for statistical machine translation

Thomas Meyer

Machine Translation (MT) has progressed tremendously in the past two decades. The rule-based and interlingua approaches have been superseded by statistical models, which learn the most likely translations from large parallel corpora. System design does not ...

EPFL2015