10 papers
Evaluating Counterfactual Strategic Reasoning in Large Language Models
Dimitrios Georgousis, Maria Lymperaiou, Angeliki Dimitriou +2
We evaluate Large Language Models (LLMs) in repeated game-theoretic settings to assess whether strategic performance reflects genuine reasoning or reliance on memorized patterns. W…
U-CECE: A Universal Multi-Resolution Framework for Conceptual Counterfactual Explanations
Angeliki Dimitriou, Nikolaos Chaidos, Maria Lymperaiou +2
As AI models grow more complex, explainability is essential for building trust, yet concept-based counterfactual methods still face a trade-off between expressivity and efficiency.…
ATLAS: Adaptive Trading with LLM AgentS Through Dynamic Prompt Optimization and Multi-Agent Coordination
Charidimos Papadakis, Angeliki Dimitriou, Giorgos Filandrianos +3
Large language models show promise for financial decision-making, yet deploying them as autonomous trading agents raises fundamental challenges: how to adapt instructions when rewa…
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…
Sparse Computations in Deep Learning Inference
Ioanna Tasou, Panagiotis Mpakos, Angelos Vlachos +25
The computational demands of modern Deep Neural Networks (DNNs) are immense and constantly growing. While training costs usually capture public attention, inference demands are als…
Bias Beware: The Impact of Cognitive Biases on LLM-Driven Product Recommendations
Giorgos Filandrianos, Angeliki Dimitriou, Maria Lymperaiou +2
The advent of Large Language Models (LLMs) has revolutionized product recommenders, yet their susceptibility to adversarial manipulation poses critical challenges, particularly in…