most citedSeq2Emo for Multi-label Emotion Classification Based on Latent Variable Chains Transformation

18 citations · 24 across the 3 of their papers we have counts for

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5 papers

cs.CL20201 cited

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…

cs.CL201918 cited

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…

cs.CL2019

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…

cs.CL2019

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…

cs.CL20195 cited

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.…