activity
20192023
most citedToolformer: Language Models Can Teach Themselves to Use Tools

400 citations · 914 across the 16 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

cs.CL2020

Toward Stance-based Personas for Opinionated Dialogues

Thomas Scialom, Serra Sinem Tekiroglu, Jacopo Staiano +1

In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations. Still, the…

cs.CL2020★ 27 cited

Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering

Arij Riabi, Thomas Scialom, Rachel Keraron +3

Coupled with the availability of large scale datasets, deep learning architectures have enabled rapid progress on the Question Answering task. However, most of those datasets are i…

cs.CL2020★ 6 cited

Project PIAF: Building a Native French Question-Answering Dataset

Rachel Keraron, Guillaume Lancrenon, Mathilde Bras +5

Motivated by the lack of data for non-English languages, in particular for the evaluation of downstream tasks such as Question Answering, we present a participatory effort to colle…

cs.CL2020★ 6 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★ 5 cited

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…