Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Bordes, Antoine"'
Autor:
Fan, Angela, Piktus, Aleksandra, Petroni, Fabio, Wenzek, Guillaume, Saeidi, Marzieh, Vlachos, Andreas, Bordes, Antoine, Riedel, Sebastian
Fact checking at scale is difficult -- while the number of active fact checking websites is growing, it remains too small for the needs of the contemporary media ecosystem. However, despite good intentions, contributions from volunteers are often err
Externí odkaz:
http://arxiv.org/abs/2011.05448
Autor:
Roller, Stephen, Boureau, Y-Lan, Weston, Jason, Bordes, Antoine, Dinan, Emily, Fan, Angela, Gunning, David, Ju, Da, Li, Margaret, Poff, Spencer, Ringshia, Pratik, Shuster, Kurt, Smith, Eric Michael, Szlam, Arthur, Urbanek, Jack, Williamson, Mary
We present our view of what is necessary to build an engaging open-domain conversational agent: covering the qualities of such an agent, the pieces of the puzzle that have been built so far, and the gaping holes we have not filled yet. We present a b
Externí odkaz:
http://arxiv.org/abs/2006.12442
Autor:
Alva-Manchego, Fernando, Martin, Louis, Bordes, Antoine, Scarton, Carolina, Sagot, Benoît, Specia, Lucia
In order to simplify a sentence, human editors perform multiple rewriting transformations: they split it into several shorter sentences, paraphrase words (i.e. replacing complex words or phrases by simpler synonyms), reorder components, and/or delete
Externí odkaz:
http://arxiv.org/abs/2005.00481
Progress in sentence simplification has been hindered by a lack of labeled parallel simplification data, particularly in languages other than English. We introduce MUSS, a Multilingual Unsupervised Sentence Simplification system that does not require
Externí odkaz:
http://arxiv.org/abs/2005.00352
Various machine learning tasks can benefit from access to external information of different modalities, such as text and images. Recent work has focused on learning architectures with large memories capable of storing this knowledge. We propose augme
Externí odkaz:
http://arxiv.org/abs/2004.12744
Query-based open-domain NLP tasks require information synthesis from long and diverse web results. Current approaches extractively select portions of web text as input to Sequence-to-Sequence models using methods such as TF-IDF ranking. We propose co
Externí odkaz:
http://arxiv.org/abs/1910.08435
Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical. It is often considered an all-purpose generic task where the same simplification is suita
Externí odkaz:
http://arxiv.org/abs/1910.02677
Autor:
Martin, Louis, Humeau, Samuel, Mazaré, Pierre-Emmanuel, Bordes, Antoine, de La Clergerie, Éric Villemonte, Sagot, Benoît
Publikováno v:
1st Workshop on Automatic Text Adaptation (ATA), Nov 2018, Tilburg, Netherlands. https://www.ida.liu.se/~evere22/ATA-18/
The evaluation of text simplification (TS) systems remains an open challenge. As the task has common points with machine translation (MT), TS is often evaluated using MT metrics such as BLEU. However, such metrics require high quality reference data,
Externí odkaz:
http://arxiv.org/abs/1901.10746
The majority of conversations a dialogue agent sees over its lifetime occur after it has already been trained and deployed, leaving a vast store of potential training signal untapped. In this work, we propose the self-feeding chatbot, a dialogue agen
Externí odkaz:
http://arxiv.org/abs/1901.05415
To achieve the long-term goal of machines being able to engage humans in conversation, our models should captivate the interest of their speaking partners. Communication grounded in images, whereby a dialogue is conducted based on a given photo, is a
Externí odkaz:
http://arxiv.org/abs/1811.00945