activity
20232025
most citedEvaluating Embeddings for One-Shot Classification of Doctor-AI Consultations

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Detecting Hope Across Languages: Multiclass Classification for Positive Online Discourse

T. O. Abiola, K. D. Abiodun, O. E. Olumide +3

The detection of hopeful speech in social media has emerged as a critical task for promoting positive discourse and well-being. In this paper, we present a machine learning approac…

cs.CL20241 cited

Evaluating Embeddings for One-Shot Classification of Doctor-AI Consultations

Olumide Ebenezer Ojo, Olaronke Oluwayemisi Adebanji, Alexander Gelbukh +2

Effective communication between healthcare providers and patients is crucial to providing high-quality patient care. In this work, we investigate how Doctor-written and AI-generate…

cs.CL20241 cited

MEDs for PETs: Multilingual Euphemism Disambiguation for Potentially Euphemistic Terms

Patrick Lee, Alain Chirino Trujillo, Diana Cuevas Plancarte +6

This study investigates the computational processing of euphemisms, a universal linguistic phenomenon, across multiple languages. We train a multilingual transformer model (XLM-RoB…

cs.CL2023

Legend at ArAIEval Shared Task: Persuasion Technique Detection using a Language-Agnostic Text Representation Model

Olumide E. Ojo, Olaronke O. Adebanji, Hiram Calvo +5

In this paper, we share our best performing submission to the Arabic AI Tasks Evaluation Challenge (ArAIEval) at ArabicNLP 2023. Our focus was on Task 1, which involves identifying…

cs.CL2023

MedAI Dialog Corpus (MEDIC): Zero-Shot Classification of Doctor and AI Responses in Health Consultations

Olumide E. Ojo, Olaronke O. Adebanji, Alexander Gelbukh +2

Zero-shot classification enables text to be classified into classes not seen during training. In this study, we examine the efficacy of zero-shot learning models in classifying hea…