Publications associées à Pronoun Translation and Prediction with or without Coreference Links

Publications associées (21)

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

From scattered sources to comprehensive technology landscape : A recommendation-based retrieval approach

Karl Aberer, Chi Thang Duong

Mapping the technology landscape is crucial for market actors to take informed investment decisions. However, given the large amount of data on the Web and its subsequent information overload, manually retrieving information is a seemingly ineffective and ...

ELSEVIER2023

Dense Image-based Predictions for Comics Analysis

Deblina Bhattacharjee

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

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents

Maud Ehrmann, Matteo Romanello

We present the HIPE-2022 shared task on named entity processing in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 evaluation lab, this edition confronts systems with the challenges of dealing with more languages, learn ...

Springer International Publishing2022

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

PARSINLU: A Suite of Language Understanding Challenges for Persian

Rabeeh Karimi Mahabadi

Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of the wid ...

2021

Interpreting Language Models Through Knowledge Graph Extraction

Martin Jaggi, Vinitra Swamy, Angeliki Romanou

Transformer-based language models trained on large text corpora have enjoyed immense popularity in the natural language processing community and are commonly used as a starting point for downstream tasks. While these models are undeniably useful, it is a c ...

2021

Overview of CLEF HIPE 2020: Named Entity Recognition and Linking on Historical Newspapers

Maud Ehrmann, Matteo Romanello

This paper presents an overview of the first edition of HIPE (Identifying Historical People, Places and other Entities), a pioneering shared task dedicated to the evaluation of named entity processing on historical newspapers in French, German and English. ...

Springer2020

Extended Overview of CLEF HIPE 2020: Named Entity Processing on Historical Newspapers

Maud Ehrmann, Matteo Romanello

This paper presents an extended overview of the first edition of HIPE (Identifying Historical People, Places and other Entities), a pioneering shared task dedicated to the evaluation of named entity processing on historical newspapers in French, German and ...

CEUR-WS2020

Approaching Ontology Alignment through Representation Learning to Bridge the Semantic Gap in Engineering Applications

Prodromos Kolyvakis

The current information landscape is characterised by a vast amount of relatively semantically homogeneous, when observed in isolation, data silos that are, however, drastically semantically fragmented when considered as a whole. Within each data silo, inf ...

EPFL2020

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

Christian O'Reilly, Elisabetta Iavarone

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousa ...

Springer2019

Transfer Learning from Pre-trained BERT for Pronoun Resolution

Qianqian Qiao, Xingce Bao

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

dhSegment: A generic deep-learning approach for document segmentation

Frédéric Kaplan, Sofia Ares Oliveira, Benoît Laurent Auguste Seguin

In recent years there have been multiple successful attempts tackling document processing problems separately by designing task specific hand-tuned strategies. We argue that the diversity of historical document processing tasks prohibits to solve them one ...

IEEE2018

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017

The SUMMA Platform Prototype

Philip Neil Garner, Hervé Bourlard, Andrei Popescu-Belis, Nikolaos Pappas, Sibo Tong, Yang Wang, Lesly Sadiht Miculicich Werlen

We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadca ...

Association for Computational Linguistics2017

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

Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation

Marina Boia

While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance. Automated sentiment analysis is a typical example: while there are techniques tha ...

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