no code implementations • 27 Jun 2024 • Tosin Adewumi, Lama Alkhaled, Namrata Gurung, Goya van Boven, Irene Pagliai
Our method involved two slightly different search queries on two reputable search engines, Google Scholar and Web of Science (WoS), which revealed that for the queries 'Fairness and bias in Large Multimodal Models' and 'Fairness and bias in Large Language Models', 33, 400 and 538, 000 links are the initial results, respectively, for Scholar while 4 and 50 links are the initial results, respectively, for WoS.
1 code implementation • 7 Apr 2024 • Irene Pagliai, Goya van Boven, Tosin Adewumi, Lama Alkhaled, Namrata Gurung, Isabella Södergren, Elisa Barney
We introduce new large labeled datasets on bias in 3 languages and show in experiments that bias exists in all 10 datasets of 5 languages evaluated, including benchmark datasets on the English GLUE/SuperGLUE leaderboards.
no code implementations • 6 Apr 2024 • Tosin Adewumi, Nudrat Habib, Lama Alkhaled, Elisa Barney
We then randomly sampled 162 chunks for human evaluation from each of the annotated books, based on the error margin of 7% and a confidence level of 95% for the book with the most chunks (Great Expectations by Charles Dickens, having 922 chunks).
no code implementations • 22 Mar 2024 • Hamam Mokayed, Rajkumar Saini, Oluwatosin Adewumi, Lama Alkhaled, Bjorn Backe, Palaiahnakote Shivakumara, Olle Hagner, Yan Chai Hum
This paper addresses the critical challenge of vehicle detection in the harsh winter conditions in the Nordic regions, characterized by heavy snowfall, reduced visibility, and low lighting.
1 code implementation • 1 Feb 2024 • Tosin Adewumi, Nudrat Habib, Lama Alkhaled, Elisa Barney
We introduce Instruction Document Visual Question Answering (iDocVQA) dataset and Large Language Document (LLaDoc) model, for training Language-Vision (LV) models for document analysis and predictions on document images, respectively.
no code implementations • 15 Dec 2023 • Tosin Adewumi, Lama Alkhaled, Claudia Buck, Sergio Hernandez, Saga Brilioth, Mkpe Kekung, Yelvin Ragimov, Elisa Barney
The results show two things: (1) ProCoT stimulates creative/critical thinking and writing of students through engagement with LLMs when we compare the LLM-only output to ProCoT output and (2) ProCoT can prevent cheating because of clear limitations in existing LLMs, particularly ChatGPT, when we compare students' ProCoT output to LLM ProCoT output.
no code implementations • 16 Nov 2023 • Jiayi Wang, David Ifeoluwa Adelani, Sweta Agrawal, Marek Masiak, Ricardo Rei, Eleftheria Briakou, Marine Carpuat, Xuanli He, Sofia Bourhim, Andiswa Bukula, Muhidin Mohamed, Temitayo Olatoye, Tosin Adewumi, Hamam Mokayed, Christine Mwase, Wangui Kimotho, Foutse Yuehgoh, Anuoluwapo Aremu, Jessica Ojo, Shamsuddeen Hassan Muhammad, Salomey Osei, Abdul-Hakeem Omotayo, Chiamaka Chukwuneke, Perez Ogayo, Oumaima Hourrane, Salma El Anigri, Lolwethu Ndolela, Thabiso Mangwana, Shafie Abdi Mohamed, Ayinde Hassan, Oluwabusayo Olufunke Awoyomi, Lama Alkhaled, sana al-azzawi, Naome A. Etori, Millicent Ochieng, Clemencia Siro, Samuel Njoroge, Eric Muchiri, Wangari Kimotho, Lyse Naomi Wamba Momo, Daud Abolade, Simbiat Ajao, Iyanuoluwa Shode, Ricky Macharm, Ruqayya Nasir Iro, Saheed S. Abdullahi, Stephen E. Moore, Bernard Opoku, Zainab Akinjobi, Abeeb Afolabi, Nnaemeka Obiefuna, Onyekachi Raphael Ogbu, Sam Brian, Verrah Akinyi Otiende, Chinedu Emmanuel Mbonu, Sakayo Toadoum Sari, Yao Lu, Pontus Stenetorp
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as BLEU, which typically show a weaker correlation with human judgments.
no code implementations • 27 Apr 2023 • Hamam Mokayed, Palaiahnakote Shivakumara, Lama Alkhaled, Rajkumar Saini, Muhammad Zeshan Afzal, Yan Chai Hum, Marcus Liwicki
Vehicle detection in real-time scenarios is challenging because of the time constraints and the presence of multiple types of vehicles with different speeds, shapes, structures, etc.
1 code implementation • 8 Apr 2023 • Lama Alkhaled, Tosin Adewumi, Sana Sabah Sabry
We introduce bipol, a new metric with explainability, for estimating social bias in text data.
2 code implementations • 28 Jan 2023 • Tosin Adewumi, Isabella Södergren, Lama Alkhaled, Sana Sabah Sabry, Foteini Liwicki, Marcus Liwicki
Hence, we also contribute a new, large Swedish bias-labelled dataset (of 2 million samples), translated from the English version and train the SotA mT5 model on it.
no code implementations • SemEval (NAACL) 2022 • Tosin Adewumi, Lama Alkhaled, Hamam Mokayed, Foteini Liwicki, Marcus Liwicki
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.