25 citations · 71 across the 6 of their papers we have counts for
7 papers
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier +2
Due to the discrete nature of words, language GANs require to be optimized from rewards provided by discriminator networks, via reinforcement learning methods. This is a much harde…
QuestEval: Summarization Asks for Fact-based Evaluation
Thomas Scialom, Paul-Alexis Dray, Patrick Gallinari +4
Summarization evaluation remains an open research problem: current metrics such as ROUGE are known to be limited and to correlate poorly with human judgments. To alleviate this iss…
ColdGANs: Taming Language GANs with Cautious Sampling Strategies
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier +2
Training regimes based on Maximum Likelihood Estimation (MLE) suffer from known limitations, often leading to poorly generated text sequences. At the root of these limitations is t…
MLSUM: The Multilingual Summarization Corpus
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier +2
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages --…
What BERT Sees: Cross-Modal Transfer for Visual Question Generation
Thomas Scialom, Patrick Bordes, Paul-Alexis Dray +2
Pre-trained language models have recently contributed to significant advances in NLP tasks. Recently, multi-modal versions of BERT have been developed, using heavy pre-training rel…
Discriminative Adversarial Search for Abstractive Summarization
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier +2
We introduce a novel approach for sequence decoding, Discriminative Adversarial Search (DAS), which has the desirable properties of alleviating the effects of exposure bias without…