752 citations · 820 across the 21 of their papers we have counts for
8 papers · 1 filter
Disentangling semantics in language through VAEs and a certain architectural choice
Ghazi Felhi, Joseph Le Roux, Djamé Seddah
We present an unsupervised method to obtain disentangled representations of sentences that single out semantic content. Using modified Transformers as building blocks, we train a V…
QUACKIE: A NLP Classification Task With Ground Truth Explanations
Yves Rychener, Xavier Renard, Djamé Seddah +2
NLP Interpretability aims to increase trust in model predictions. This makes evaluating interpretability approaches a pressing issue. There are multiple datasets for evaluating NLP…
On the Granularity of Explanations in Model Agnostic NLP Interpretability
Yves Rychener, Xavier Renard, Djamé Seddah +2
Current methods for Black-Box NLP interpretability, like LIME or SHAP, are based on altering the text to interpret by removing words and modeling the Black-Box response. In this pa…
Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations
Manuela Sanguinetti, Lauren Cassidy, Cristina Bosco +7
This article presents a discussion on the main linguistic phenomena which cause difficulties in the analysis of user-generated texts found on the web and in social media, and propo…
Controlling the Interaction Between Generation and Inference in Semi-Supervised Variational Autoencoders Using Importance Weighting
Ghazi Felhi, Joseph Leroux, Djamé Seddah
Even though Variational Autoencoders (VAEs) are widely used for semi-supervised learning, the reason why they work remains unclear. In fact, the addition of the unsupervised object…
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models
Benjamin Muller, Antonis Anastasopoulos, Benoît Sagot +1
Transfer learning based on pretraining language models on a large amount of raw data has become a new norm to reach state-of-the-art performance in NLP. Still, it remains unclear h…
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…
Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi
Benjamin Muller, Benoit Sagot, Djamé Seddah
Building natural language processing systems for non standardized and low resource languages is a difficult challenge. The recent success of large-scale multilingual pretrained lan…