1 citations · 1 across the 9 of their papers we have counts for
10 papers
OmouAI: Argumentative Human-AI Policy Deliberation with Simulated Personas
Stylianos Loukas Vasileiou, Antonio Rago, William Yeoh +1
Debates amongst agents driven by large language models (LLMs) have demonstrated vast potential in various applications, but when these interactions include humans and take place in…
Argumentative Human-AI Decision-Making: Toward AI Agents That Reason With Us, Not For Us
Stylianos Loukas Vasileiou, Antonio Rago, Francesca Toni +1
Computational argumentation offers formal frameworks for transparent, verifiable reasoning but has traditionally been limited by its reliance on domain-specific information and ext…
How Do People Revise Inconsistent Beliefs? Examining Belief Revision in Humans with User Studies
Stylianos Loukas Vasileiou, Antonio Rago, Maria Vanina Martinez +1
Understanding how humans revise their beliefs in light of new information is crucial for developing AI systems which can effectively model, and thus align with, human reasoning. Wh…
Does Your AI Agent Get You? A Personalizable Framework for Approximating Human Models from Argumentation-based Dialogue Traces
Yinxu Tang, Stylianos Loukas Vasileiou, William Yeoh
Explainable AI is increasingly employing argumentation methods to facilitate interactive explanations between AI agents and human users. While existing approaches typically rely on…
A Methodology for Incompleteness-Tolerant and Modular Gradual Semantics for Argumentative Statement Graphs
Antonio Rago, Stylianos Loukas Vasileiou, Francesca Toni +2
Gradual semantics (GS) have demonstrated great potential in argumentation, in particular for deploying quantitative bipolar argumentation frameworks (QBAFs) in a number of real-wor…
TRACE-CS: A Hybrid Logic-LLM System for Explainable Course Scheduling
Stylianos Loukas Vasileiou, William Yeoh
We present TRACE-CS, a novel hybrid system that combines symbolic reasoning with large language models (LLMs)to address contrastive queries in course scheduling problems. TRACE-CS…
Approximating Human Models During Argumentation-based Dialogues
Yinxu Tang, Stylianos Loukas Vasileiou, William Yeoh
Explainable AI Planning (XAIP) aims to develop AI agents that can effectively explain their decisions and actions to human users, fostering trust and facilitating human-AI collabor…
Predicting Customer Goals in Financial Institution Services: A Data-Driven LSTM Approach
Andrew Estornell, Stylianos Loukas Vasileiou, William Yeoh +2
In today's competitive financial landscape, understanding and anticipating customer goals is crucial for institutions to deliver a personalized and optimized user experience. This…
Human-Aware Belief Revision: A Cognitively Inspired Framework for Explanation-Guided Revision of Human Models
Stylianos Loukas Vasileiou, William Yeoh
Traditional belief revision frameworks often rely on the principle of minimalism, which advocates minimal changes to existing beliefs. However, research in human cognition suggests…
On Generating Monolithic and Model Reconciling Explanations in Probabilistic Scenarios
Stylianos Loukas Vasileiou, William Yeoh, Alessandro Previti +1
Explanation generation frameworks aim to make AI systems' decisions transparent and understandable to human users. However, generating explanations in uncertain environments charac…