5 citations · 11 across the 7 of their papers we have counts for
7 papers
iSee: Advancing Multi-Shot Explainable AI Using Case-based Recommendations
Anjana Wijekoon, Nirmalie Wiratunga, David Corsar +7
Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Recent findings suggest that a single explainer may not meet the dive…
XEQ Scale for Evaluating XAI Experience Quality
Anjana Wijekoon, Nirmalie Wiratunga, David Corsar +4
Explainable Artificial Intelligence (XAI) aims to improve the transparency of autonomous decision-making through explanations. Recent literature has emphasised users' need for holi…
Tell me more: Intent Fulfilment Framework for Enhancing User Experiences in Conversational XAI
Anjana Wijekoon, David Corsar, Nirmalie Wiratunga +2
The evolution of Explainable Artificial Intelligence (XAI) has emphasised the significance of meeting diverse user needs. The approaches to identifying and addressing these needs m…
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering
Nirmalie Wiratunga, Ramitha Abeyratne, Lasal Jayawardena +6
Retrieval-Augmented Generation (RAG) enhances Large Language Model (LLM) output by providing prior knowledge as context to input. This is beneficial for knowledge-intensive and exp…
Clinical Dialogue Transcription Error Correction using Seq2Seq Models
Gayani Nanayakkara, Nirmalie Wiratunga, David Corsar +2
Good communication is critical to good healthcare. Clinical dialogue is a conversation between health practitioners and their patients, with the explicit goal of obtaining and shar…
DisCERN:Discovering Counterfactual Explanations using Relevance Features from Neighbourhoods
Nirmalie Wiratunga, Anjana Wijekoon, Ikechukwu Nkisi-Orji +3
Counterfactual explanations focus on "actionable knowledge" to help end-users understand how a machine learning outcome could be changed to a more desirable outcome. For this purpo…