most citedQuestEval: Summarization Asks for Fact-based Evaluation

25 citations · 32 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL20211 cited

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…

cs.CL202125 cited

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…

cs.CL20206 cited

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…

cs.CL2020

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 --…

cs.CL2020

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…

cs.CL2020

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…