9 citations · 25 across the 44 of their papers we have counts for
14 papers · 1 filter
Enhancing adversarial robustness in Natural Language Inference using explanations
Alexandros Koulakos, Maria Lymperaiou, Giorgos Filandrianos +1
The surge of state-of-the-art Transformer-based models has undoubtedly pushed the limits of NLP model performance, excelling in a variety of tasks. We cast the spotlight on the und…
BERTtime Stories: Investigating the Role of Synthetic Story Data in Language Pre-training
Nikitas Theodoropoulos, Giorgos Filandrianos, Vassilis Lyberatos +2
We describe our contribution to the Strict and Strict-Small tracks of the 2nd iteration of the BabyLM Challenge. The shared task is centered around efficient pre-training given dat…
"I Never Said That": A dataset, taxonomy and baselines on response clarity classification
Konstantinos Thomas, Giorgos Filandrianos, Maria Lymperaiou +2
Equivocation and ambiguity in public speech are well-studied discourse phenomena, especially in political science and analysis of political interviews. Inspired by the well-grounde…
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…
RISCORE: Enhancing In-Context Riddle Solving in Language Models through Context-Reconstructed Example Augmentation
Ioannis Panagiotopoulos, Giorgos Filandrianos, Maria Lymperaiou +1
Riddle-solving requires advanced reasoning skills, pushing LLMs to engage in abstract thinking and creative problem-solving, often revealing limitations in their cognitive abilitie…
ARPA: A Novel Hybrid Model for Advancing Visual Word Disambiguation Using Large Language Models and Transformers
Aristi Papastavrou, Maria Lymperaiou, Giorgos Stamou
In the rapidly evolving fields of natural language processing and computer vision, Visual Word Sense Disambiguation (VWSD) stands as a critical, yet challenging task. The quest for…
Optimal and efficient text counterfactuals using Graph Neural Networks
Dimitris Lymperopoulos, Maria Lymperaiou, Giorgos Filandrianos +1
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…
Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models
Georgia Argyrou, Angeliki Dimitriou, Maria Lymperaiou +2
The advent of artificial intelligence has contributed in a groundbreaking transformation of the fashion industry, redefining creativity and innovation in unprecedented ways. This w…
AILS-NTUA at SemEval-2024 Task 6: Efficient model tuning for hallucination detection and analysis
Natalia Grigoriadou, Maria Lymperaiou, Giorgos Filandrianos +1
In this paper, we present our team's submissions for SemEval-2024 Task-6 - SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes. The participants…
AILS-NTUA at SemEval-2024 Task 9: Cracking Brain Teasers: Transformer Models for Lateral Thinking Puzzles
Ioannis Panagiotopoulos, Giorgos Filandrianos, Maria Lymperaiou +1
In this paper, we outline our submission for the SemEval-2024 Task 9 competition: 'BRAINTEASER: A Novel Task Defying Common Sense'. We engage in both sub-tasks: Sub-task A-Sentence…
Masked Generative Story Transformer with Character Guidance and Caption Augmentation
Christos Papadimitriou, Giorgos Filandrianos, Maria Lymperaiou +1
Story Visualization (SV) is a challenging generative vision task, that requires both visual quality and consistency between different frames in generated image sequences. Previous…
Structure Your Data: Towards Semantic Graph Counterfactuals
Angeliki Dimitriou, Maria Lymperaiou, Giorgos Filandrianos +2
Counterfactual explanations (CEs) based on concepts are explanations that consider alternative scenarios to understand which high-level semantic features contributed to particular…
Puzzle Solving using Reasoning of Large Language Models: A Survey
Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos +1
Exploring the capabilities of Large Language Models (LLMs) in puzzle solving unveils critical insights into their potential and challenges in AI, marking a significant step towards…
Graph Edits for Counterfactual Explanations: A comparative study
Angeliki Dimitriou, Nikolaos Chaidos, Maria Lymperaiou +1
Counterfactuals have been established as a popular explainability technique which leverages a set of minimal edits to alter the prediction of a classifier. When considering concept…