9 citations · 25 across the 44 of their papers we have counts for
13 papers · 1 filter
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…
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…
Analyze-Prompt-Reason: A Collaborative Agent-Based Framework for Multi-Image Vision-Language Reasoning
Angelos Vlachos, Giorgos Filandrianos, Maria Lymperaiou +4
We present a Collaborative Agent-Based Framework for Multi-Image Reasoning. Our approach tackles the challenge of interleaved multimodal reasoning across diverse datasets and task…
StockSim: A Dual-Mode Order-Level Simulator for Evaluating Multi-Agent LLMs in Financial Markets
Charidimos Papadakis, Giorgos Filandrianos, Angeliki Dimitriou +3
We present StockSim, an open-source simulation platform for systematic evaluation of large language models (LLMs) in realistic financial decision-making scenarios. Unlike previous…
PAKTON: A Multi-Agent Framework for Question Answering in Long Legal Agreements
Petros Raptopoulos, Giorgos Filandrianos, Maria Lymperaiou +1
Contract review is a complex and time-intensive task that typically demands specialized legal expertise, rendering it largely inaccessible to non-experts. Moreover, legal interpret…
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…
AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question Answering
Andreas Evangelatos, Giorgos Filandrianos, Maria Lymperaiou +2
In this paper, we present our submission to SemEval-2025 Task 8: Question Answering over Tabular Data. This task, evaluated on the DataBench dataset, assesses Large Language Models…
AILS-NTUA at SemEval-2025 Task 4: Parameter-Efficient Unlearning for Large Language Models using Data Chunking
Iraklis Premptis, Maria Lymperaiou, Giorgos Filandrianos +3
The Unlearning Sensitive Content from Large Language Models task aims to remove targeted datapoints from trained models while minimally affecting their general knowledge. In our wo…
AILS-NTUA at SemEval-2025 Task 3: Leveraging Large Language Models and Translation Strategies for Multilingual Hallucination Detection
Dimitra Karkani, Maria Lymperaiou, Giorgos Filandrianos +3
Multilingual hallucination detection stands as an underexplored challenge, which the Mu-SHROOM shared task seeks to address. In this work, we propose an efficient, training-free LL…
Conceptual Contrastive Edits in Textual and Vision-Language Retrieval
Maria Lymperaiou, Giorgos Stamou
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 e…
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…
Pitfalls of Scale: Investigating the Inverse Task of Redefinition in Large Language Models
Elena Stringli, Maria Lymperaiou, Giorgos Filandrianos +2
Inverse tasks can uncover potential reasoning gaps as Large Language Models (LLMs) scale up. In this work, we explore the redefinition task, in which we assign alternative values t…
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…