18 citations · 24 across the 4 of their papers we have counts for
6 papers · 1 filter
Named Entity Recognition for Partially Annotated Datasets
Michael Strobl, Amine Trabelsi, Osmar Zaiane
The most common Named Entity Recognizers are usually sequence taggers trained on fully annotated corpora, i.e. the class of all words for all entities is known. Partially annotated…
ANA at SemEval-2020 Task 4: mUlti-task learNIng for cOmmonsense reasoNing (UNION)
Anandh Perumal, Chenyang Huang, Amine Trabelsi +1
In this paper, we describe our mUlti-task learNIng for cOmmonsense reasoNing (UNION) system submitted for Task C of the SemEval2020 Task 4, which is to generate a reason explaining…
Seq2Emo for Multi-label Emotion Classification Based on Latent Variable Chains Transformation
Chenyang Huang, Amine Trabelsi, Xuebin Qin +2
Emotion detection in text is an important task in NLP and is essential in many applications. Most of the existing methods treat this task as a problem of single-label multi-class t…
Self-Attentional Models Application in Task-Oriented Dialogue Generation Systems
Mansour Saffar Mehrjardi, Amine Trabelsi, Osmar R. Zaiane
Self-attentional models are a new paradigm for sequence modelling tasks which differ from common sequence modelling methods, such as recurrence-based and convolution-based sequence…
Contrastive Reasons Detection and Clustering from Online Polarized Debate
Amine Trabelsi, Osmar R. Zaiane
This work tackles the problem of unsupervised modeling and extraction of the main contrastive sentential reasons conveyed by divergent viewpoints on polarized issues. It proposes a…
ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT
Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane
This paper describes the system submitted by ANA Team for the SemEval-2019 Task 3: EmoContext. We propose a novel Hierarchical LSTMs for Contextual Emotion Detection (HRLCE) model.…