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20212026
most citedPuzzle Solving using Reasoning of Large Language Models: A Survey

9 citations · 43 across the 69 of their papers we have counts for

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cs.CV2025

Through the PRISm: Importance-Aware Scene Graphs for Image Retrieval

Dimitrios Georgoulopoulos, Nikolaos Chaidos, Angeliki Dimitriou +1

Accurately retrieving images that are semantically similar remains a fundamental challenge in computer vision, as traditional methods often fail to capture the relational and conte…

cs.CV2025

V-CECE: Visual Counterfactual Explanations via Conceptual Edits

Nikolaos Spanos, Maria Lymperaiou, Giorgos Filandrianos +3

Recent black-box counterfactual generation frameworks fail to take into account the semantic content of the proposed edits, while relying heavily on training to guide the generatio…

cs.CV2025

SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval

Nikolaos Chaidos, Angeliki Dimitriou, Maria Lymperaiou +1

Despite the dominance of convolutional and transformer-based architectures in image-to-image retrieval, these models are prone to biases arising from low-level visual features, suc…

cs.CV2025

Explaining Vision GNNs: A Semantic and Visual Analysis of Graph-based Image Classification

Nikolaos Chaidos, Angeliki Dimitriou, Nikolaos Spanos +2

Graph Neural Networks (GNNs) have emerged as an efficient alternative to convolutional approaches for vision tasks such as image classification, leveraging patch-based representati…

cs.CV2025

HalCECE: A Framework for Explainable Hallucination Detection through Conceptual Counterfactuals in Image Captioning

Maria Lymperaiou, Giorgos Filandrianos, Angeliki Dimitriou +2

In the dynamic landscape of artificial intelligence, the exploration of hallucinations within vision-language (VL) models emerges as a critical frontier. This work delves into the…

cs.CV2024

Prompt2Fashion: An automatically generated fashion dataset

Georgia Argyrou, Angeliki Dimitriou, Maria Lymperaiou +2

Despite the rapid evolution and increasing efficacy of language and vision generative models, there remains a lack of comprehensive datasets that bridge the gap between personalize…