222 citations · 284 across the 13 of their papers we have counts for
9 papers · 1 filter
Explainable AI: Context-Aware Layer-Wise Integrated Gradients for Explaining Transformer Models
Melkamu Abay Mersha, Jugal Kalita
Transformer models achieve state-of-the-art performance across domains and tasks, yet their deeply layered representations make their predictions difficult to interpret. Existing e…
Semantic-Driven Topic Modeling for Analyzing Creativity in Virtual Brainstorming
Melkamu Abay Mersha, Jugal Kalita
Virtual brainstorming sessions have become a central component of collaborative problem solving, yet the large volume and uneven distribution of ideas often make it difficult to ex…
Explainable AI: XAI-Guided Context-Aware Data Augmentation
Melkamu Abay Mersha, Mesay Gemeda Yigezu, Atnafu Lambebo Tonja +4
Explainable AI (XAI) has emerged as a powerful tool for improving the performance of AI models, going beyond providing model transparency and interpretability. The scarcity of labe…
A Unified Framework with Novel Metrics for Evaluating the Effectiveness of XAI Techniques in LLMs
Melkamu Abay Mersha, Mesay Gemeda Yigezu, Hassan Shakil +3
The increasing complexity of LLMs presents significant challenges to their transparency and interpretability, necessitating the use of eXplainable AI (XAI) techniques to enhance tr…
Evaluating the Effectiveness of XAI Techniques for Encoder-Based Language Models
Melkamu Abay Mersha, Mesay Gemeda Yigezu, Jugal Kalita
The black-box nature of large language models (LLMs) necessitates the development of eXplainable AI (XAI) techniques for transparency and trustworthiness. However, evaluating these…
Explainability in Neural Networks for Natural Language Processing Tasks
Melkamu Mersha, Mingiziem Bitewa, Tsion Abay +1
Neural networks are widely regarded as black-box models, creating significant challenges in understanding their inner workings, especially in natural language processing (NLP) appl…
Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI
Mesay Gemeda Yigezu, Melkamu Abay Mersha, Girma Yohannis Bade +3
The proliferation of fake news has emerged as a significant threat to the integrity of information dissemination, particularly on social media platforms. Misinformation can spread…
Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms
Melkamu Abay Mersha, Mesay Gemeda yigezu, Jugal Kalita
Topic modeling is a powerful technique to discover hidden topics and patterns within a collection of documents without prior knowledge. Traditional topic modeling and clustering-ba…
First Attempt at Building Parallel Corpora for Machine Translation of Northeast India's Very Low-Resource Languages
Atnafu Lambebo Tonja, Melkamu Mersha, Ananya Kalita +2
This paper presents the creation of initial bilingual corpora for thirteen very low-resource languages of India, all from Northeast India. It also presents the results of initial t…