no code implementations • COLING 2022 • Eric Austin, Osmar R. Zaïane, Christine Largeron
We present our novel, hyperparameter-free topic modelling algorithm, Community Topic.
no code implementations • 28 Oct 2022 • Nawshad Farruque, Randy Goebel, Sudhakar Sivapalan, Osmar R. Zaïane
We describe the development of a model to detect user-level clinical depression based on a user's temporal social media posts.
no code implementations • 28 Jan 2022 • Abhishek Dhankar, Osmar R. Zaïane, Francois Bolduc
Identifying fake news is a very difficult task, especially when considering the multiple modes of conveying information through text, image, video and/or audio.
2 code implementations • 14 Oct 2021 • Chenyang Huang, Hao Zhou, Osmar R. Zaïane, Lili Mou, Lei LI
How do we perform efficient inference while retaining high translation quality?
1 code implementation • SEMEVAL 2020 • Anandh Perumal, Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane
In order to generate more meaningful explanations, we propose UNION, a unified end-to-end framework, to utilize several existing commonsense datasets so that it allows a model to learn more dynamics under the scope of commonsense reasoning.
no code implementations • 6 Nov 2019 • Chenyang Huang, Amine Trabelsi, Xuebin Qin, Nawshad Farruque, Osmar R. Zaïane
Most of the existing methods treat this task as a problem of single-label multi-class text classification.
1 code implementation • SEMEVAL 2019 • Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane
This paper describes the system submitted by ANA Team for the SemEval-2019 Task 3: EmoContext.
Ranked #3 on Emotion Recognition in Conversation on EC
Emotion Recognition in Conversation General Classification +2
no code implementations • 15 Nov 2018 • Chenyang Huang, Osmar R. Zaïane
Neural network-based Open-ended conversational agents automatically generate responses based on predictive models learned from a large number of pairs of utterances.