most citedML_LTU at SemEval-2022 Task 4: T5 Towards Identifying Patronizing and Condescending Language

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

collaborators

5 papers

cs.CL2025

From the Rock Floor to the Cloud: A Systematic Survey of State-of-the-Art NLP in Battery Life Cycle

Tosin Adewumi, Martin Karlsson, Marcus Liwicki +5

We present a comprehensive systematic survey of the application of natural language processing (NLP) along the entire battery life cycle, instead of one stage or method, and introd…

cs.SD2025

Sound Signal Synthesis with Auxiliary Classifier GAN, COVID-19 cough as an example

Yahya Sherif Solayman Mohamed Saleh, Ahmed Mohammed Dabbous, Lama Alkhaled +3

One of the fastest-growing domains in AI is healthcare. Given its importance, it has been the interest of many researchers to deploy ML models into the ever-demanding healthcare do…

cs.AI20251 cited

AI Must not be Fully Autonomous

Tosin Adewumi, Lama Alkhaled, Florent Imbert +3

Autonomous Artificial Intelligence (AI) has many benefits. It also has many risks. In this work, we identify the 3 levels of autonomous AI. We are of the position that AI must not…

cs.CL2025

Findings of MEGA: Maths Explanation with LLMs using the Socratic Method for Active Learning

Tosin Adewumi, Foteini Simistira Liwicki, Marcus Liwicki +3

This paper presents an intervention study on the effects of the combined methods of (1) the Socratic method, (2) Chain of Thought (CoT) reasoning, (3) simplified gamification and (…

cs.CL20222 cited

ML_LTU at SemEval-2022 Task 4: T5 Towards Identifying Patronizing and Condescending Language

Tosin Adewumi, Lama Alkhaled, Hamam Mokayed +2

This paper describes the system used by the Machine Learning Group of LTU in subtask 1 of the SemEval-2022 Task 4: Patronizing and Condescending Language (PCL) Detection. Our syste…