2 citations · 2 across the 5 of their papers we have counts for
5 papers
Concept-based explanations of Segmentation and Detection models in Natural Disaster Management
Samar Heydari, Jawher Said, Galip Ümit Yolcu +7
Deep learning models for flood and wildfire segmentation and object detection enable precise, real-time disaster localization when deployed on embedded drone platforms. However, in…
A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents
Raghu Arghal, Fade Chen, Niall Dalton +6
Understanding an agent's goals helps explain and predict its behaviour, yet there is no established methodology for reliably attributing goals to agentic systems. We propose a fram…
Towards User-Focused Research in Training Data Attribution for Human-Centered Explainable AI
Elisa Nguyen, Johannes Bertram, Evgenii Kortukov +2
Explainable AI (XAI) aims to make AI systems more transparent, yet many practices emphasise mathematical rigour over practical user needs. We propose an alternative to this model-c…
Studying Large Language Model Behaviors Under Context-Memory Conflicts With Real Documents
Evgenii Kortukov, Alexander Rubinstein, Elisa Nguyen +1
Retrieval-augmented generation (RAG) mitigates many problems of fully parametric language models, such as temporal degradation, hallucinations, and lack of grounding. In RAG, the m…
Exploring Practitioner Perspectives On Training Data Attribution Explanations
Elisa Nguyen, Evgenii Kortukov, Jean Y. Song +1
Explainable AI (XAI) aims to provide insight into opaque model reasoning to humans and as such is an interdisciplinary field by nature. In this paper, we interviewed 10 practitione…