no code implementations • EACL (WASSA) 2021 • Shabnam Tafreshi, Orphee De Clercq, Valentin Barriere, Sven Buechel, João Sedoc, Alexandra Balahur
This paper presents the results that were obtained from the WASSA 2021 shared task on predicting empathy and emotions.
no code implementations • WASSA (ACL) 2022 • Valentin Barriere, Shabnam Tafreshi, João Sedoc, Sawsan Alqahtani
This paper presents the results that were obtained from WASSA 2022 shared task on predicting empathy, emotion, and personality in reaction to news stories.
no code implementations • AMTA 2022 • Michael Maxwell, Shabnam Tafreshi, Aquia Richburg, Balaji Kodali, Kymani Brown
In theory, this also provides style information such as bolding and italicization, but in practice, this capability is limited.
1 code implementation • 25 Apr 2024 • Saranya Krishnamoorthy, Ayush Singh, Shabnam Tafreshi
Electronic health records (EHR) even though a boon for healthcare practitioners, are growing convoluted and longer every day.
Ranked #1 on Classification on MedSecId
no code implementations • 28 Feb 2024 • Shabnam Tafreshi, Shubham Vatsal, Mona Diab
There are 7100+ active languages spoken around the world and building emotion classification for each language is labor intensive.
no code implementations • 28 Feb 2024 • Shubham Vatsal, Ayush Singh, Shabnam Tafreshi
Health insurance companies have a defined process called prior authorization (PA) which is a health plan cost-control process that requires doctors and other healthcare professionals to get clearance in advance from a health plan before performing a particular procedure on a patient in order to be eligible for payment coverage.
no code implementations • 25 May 2022 • Damilola Omitaomu, Shabnam Tafreshi, Tingting Liu, Sven Buechel, Chris Callison-Burch, Johannes Eichstaedt, Lyle Ungar, João Sedoc
Hence, we collected detailed characterization of the participants' traits, their self-reported empathetic response to news articles, their conversational partner other-report, and turn-by-turn third-party assessments of the level of self-disclosure, emotion, and empathy expressed.
no code implementations • SEMEVAL 2019 • Shabnam Tafreshi, Mona Diab
Our aim is to build a robust emotion classifier that can generalize emotion detection, which is to learn emotion cues in a noisy training environment.
no code implementations • 23 May 2019 • Shabnam Tafreshi, Mona Diab
In this paper we present an emotion classifier model submitted to the SemEval-2019 Task 3: EmoContext.
no code implementations • 24 Feb 2019 • Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard Hovy, Alan W. black, Jaime Carbonell, Graham V. Horwood, Shabnam Tafreshi, Mona Diab, Efsun S. Kayi, Noura Farra, Kathleen McKeown
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).
no code implementations • COLING 2018 • Shabnam Tafreshi, Mona Diab
Detection and classification of emotion categories expressed by a sentence is a challenging task due to subjectivity of emotion.