Maria Lymperaiou

Optimal and efficient text counterfactuals using Graph Neural Networks

2024 · arXiv (Cornell University)

As NLP models become increasingly integral to decision-making processes, the need for explainability and interpretability has become paramount. In this work, we propose a framework that achieves the aforementioned by generating semantically edited inputs, known …

Conceptual Contrastive Edits in Textual and Vision-Language Retrieval

2025 · arXiv (Cornell University)

As deep learning models grow in complexity, achieving model-agnostic interpretability becomes increasingly vital. In this work, we employ post-hoc conceptual contrastive edits to expose noteworthy patterns and biases imprinted in representations of retrieval models. We …