11 citations · 42 across the 23 of their papers we have counts for
23 papers
Counterargument for Critical Thinking as Judged by AI and Humans
Tosin Adewumi, Marcus Liwicki, Foteini Simistira Liwicki +3
This intervention study investigates the use of counterarguments in writing for critical thinking by students in the context of Generative AI (GenAI). This is especially as risks o…
On the Codesign of Scientific Experiments and Industrial Systems
Tommaso Dorigo, Pietro Vischia, Shahzaib Abbas +84
The optimization of large experiments in fundamental science, such as detectors for subnuclear physics at particle colliders, shares with the optimization of complex systems for in…
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 (…
SimBrainNet: Evaluating Brain Network Similarity for Attention Disorders
Debashis Das Chakladar, Foteini Simistira Liwicki, Rajkumar Saini
Electroencephalography (EEG)-based attention disorder research seeks to understand brain activity patterns associated with attention. Previous studies have mainly focused on identi…
Performance of data-driven inner speech decoding with same-task EEG-fMRI data fusion and bimodal models
Holly Wilson, Scott Wellington, Foteini Simistira Liwicki +13
Decoding inner speech from the brain signal via hybridisation of fMRI and EEG data is explored to investigate the performance benefits over unimodal models. Two different bimodal f…
A Comparison of Temporal Encoders for Neuromorphic Keyword Spotting with Few Neurons
Mattias Nilsson, Ton Juny Pina, Lyes Khacef +3
With the expansion of AI-powered virtual assistants, there is a need for low-power keyword spotting systems providing a "wake-up" mechanism for subsequent computationally expensive…
Bipol: Multi-axes Evaluation of Bias with Explainability in Benchmark Datasets
Tosin Adewumi, Isabella Södergren, Lama Alkhaled +3
We investigate five English NLP benchmark datasets (on the superGLUE leaderboard) and two Swedish datasets for bias, along multiple axes. The datasets are the following: Boolean Qu…
T5 for Hate Speech, Augmented Data and Ensemble
Tosin Adewumi, Sana Sabah Sabry, Nosheen Abid +2
We conduct relatively extensive investigations of automatic hate speech (HS) detection using different state-of-the-art (SoTA) baselines over 11 subtasks of 6 different datasets. O…
Deep Neural Network approaches for Analysing Videos of Music Performances
Foteini Simistira Liwicki, Richa Upadhyay, Prakash Chandra Chhipa +4
This paper presents a framework to automate the labelling process for gestures in musical performance videos with a 3D Convolutional Neural Network (CNN). While this idea was propo…
AfriWOZ: Corpus for Exploiting Cross-Lingual Transferability for Generation of Dialogues in Low-Resource, African Languages
Tosin Adewumi, Mofetoluwa Adeyemi, Aremu Anuoluwapo +17
Dialogue generation is an important NLP task fraught with many challenges. The challenges become more daunting for low-resource African languages. To enable the creation of dialogu…
Vector Representations of Idioms in Conversational Systems
Tosin Adewumi, Foteini Liwicki, Marcus Liwicki
We demonstrate, in this study, that an open-domain conversational system trained on idioms or figurative language generates more fitting responses to prompts containing idioms. Idi…
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…
State-of-the-art in Open-domain Conversational AI: A Survey
Tosin Adewumi, Foteini Liwicki, Marcus Liwicki
We survey SoTA open-domain conversational AI models with the purpose of presenting the prevailing challenges that still exist to spur future research. In addition, we provide stati…
HaT5: Hate Language Identification using Text-to-Text Transfer Transformer
Sana Sabah Sabry, Tosin Adewumi, Nosheen Abid +3
We investigate the performance of a state-of-the art (SoTA) architecture T5 (available on the SuperGLUE) and compare with it 3 other previous SoTA architectures across 5 different…
Småprat: DialoGPT for Natural Language Generation of Swedish Dialogue by Transfer Learning
Tosin Adewumi, Rickard Brännvall, Nosheen Abid +4
Building open-domain conversational systems (or chatbots) that produce convincing responses is a recognized challenge. Recent state-of-the-art (SoTA) transformer-based models for t…
Spatiotemporal Pattern Recognition in Single Mixed-Signal VLSI Neurons with Heterogeneous Dynamic Synapses
Mattias Nilsson, Foteini Liwicki, Fredrik Sandin
Mixed-signal neuromorphic processors with brain-like organization and device physics offer an ultra-low-power alternative to the unsustainable developments of conventional deep lea…
Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idioms
Tosin P. Adewumi, Roshanak Vadoodi, Aparajita Tripathy +3
We present a fairly large, Potential Idiomatic Expression (PIE) dataset for Natural Language Processing (NLP) in English. The challenges with NLP systems with regards to tasks such…
The Challenge of Diacritics in Yoruba Embeddings
Tosin P. Adewumi, Foteini Liwicki, Marcus Liwicki
The major contributions of this work include the empirical establishment of a better performance for Yoruba embeddings from undiacritized (normalized) dataset and provision of new…
Corpora Compared: The Case of the Swedish Gigaword & Wikipedia Corpora
Tosin P. Adewumi, Foteini Liwicki, Marcus Liwicki
In this work, we show that the difference in performance of embeddings from differently sourced data for a given language can be due to other factors besides data size. Natural lan…
Exploring Swedish & English fastText Embeddings for NER with the Transformer
Tosin P. Adewumi, Foteini Liwicki, Marcus Liwicki
In this paper, our main contributions are that embeddings from relatively smaller corpora can outperform ones from larger corpora and we make the new Swedish analogy test set publi…
Word2Vec: Optimal Hyper-Parameters and Their Impact on NLP Downstream Tasks
Tosin P. Adewumi, Foteini Liwicki, Marcus Liwicki
Word2Vec is a prominent model for natural language processing (NLP) tasks. Similar inspiration is found in distributed embeddings for new state-of-the-art (SotA) deep neural networ…
Synaptic Integration of Spatiotemporal Features with a Dynamic Neuromorphic Processor
Mattias Nilsson, Foteini Liwicki, Fredrik Sandin
Spiking neurons can perform spatiotemporal feature detection by nonlinear synaptic and dendritic integration of presynaptic spike patterns. Multicompartment models of non-linear de…
ICDAR 2019 Historical Document Reading Challenge on Large Structured Chinese Family Records
Rajkumar Saini, Derek Dobson, Jon Morrey +2
We propose a Historical Document Reading Challenge on Large Chinese Structured Family Records, in short ICDAR2019 HDRC CHINESE. The objective of the proposed competition is to reco…