570 citations · 2.6k across the 75 of their papers we have counts for
7 papers · 1 filter
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
Paul Roit, Johan Ferret, Lior Shani +16
Despite the seeming success of contemporary grounded text generation systems, they often tend to generate factually inconsistent text with respect to their input. This phenomenon i…
vec2text with Round-Trip Translations
Geoffrey Cideron, Sertan Girgin, Anton Raichuk +3
We investigate models that can generate arbitrary natural language text (e.g. all English sentences) from a bounded, convex and well-behaved control space. We call them universal v…
Supervised Seeded Iterated Learning for Interactive Language Learning
Yuchen Lu, Soumye Singhal, Florian Strub +2
Language drift has been one of the major obstacles to train language models through interaction. When word-based conversational agents are trained towards completing a task, they t…
End-to-End Automatic Speech Translation of Audiobooks
Alexandre Bérard, Laurent Besacier, Ali Can Kocabiyikoglu +1
We investigate end-to-end speech-to-text translation on a corpus of audiobooks specifically augmented for this task. Previous works investigated the extreme case where source langu…
LIG-CRIStAL System for the WMT17 Automatic Post-Editing Task
Alexandre Berard, Olivier Pietquin, Laurent Besacier
This paper presents the LIG-CRIStAL submission to the shared Automatic Post- Editing task of WMT 2017. We propose two neural post-editing models: a monosource model with a task-spe…
End-to-end optimization of goal-driven and visually grounded dialogue systems
Florian Strub, Harm de Vries, Jeremie Mary +3
End-to-end design of dialogue systems has recently become a popular research topic thanks to powerful tools such as encoder-decoder architectures for sequence-to-sequence learning.…
Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation
Alexandre Berard, Olivier Pietquin, Christophe Servan +1
This paper proposes a first attempt to build an end-to-end speech-to-text translation system, which does not use source language transcription during learning or decoding. We propo…