9 papers
Mitigating Semantic Drift: Evaluating LLMs' Efficacy in Psychotherapy through MI Dialogue Summarization
Vivek Kumar, Pushpraj Singh Rajawat, Eirini Ntoutsi
Recent advancements in large language models (LLMs) have shown their potential across both general and domain-specific tasks. However, there is a growing concern regarding their la…
Effector: A Python package for regional explanations
Vasilis Gkolemis, Christos Diou, Dimitris Kyriakopoulos +10
Effector is a Python package for interpreting machine learning (ML) models that are trained on tabular data through global and regional feature effects. Global effects, like Partia…
A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective
Siamak Ghodsi, Amjad Seyedi, Tai Le Quy +2
Fair graph clustering seeks partitions that respect network structure while maintaining proportional representation across sensitive groups, with applications spanning community de…
Achieving Socio-Economic Parity through the Lens of EU AI Act
Arjun Roy, Stavroula Rizou, Symeon Papadopoulos +1
Unfair treatment and discrimination are critical ethical concerns in AI systems, particularly as their adoption expands across diverse domains. Addressing these challenges, the rec…
Attention Mechanism based Cognition-level Scene Understanding
Xuejiao Tang, Wenbin Zhang
Given a question-image input, the Visual Commonsense Reasoning (VCR) model can predict an answer with the corresponding rationale, which requires inference ability from the real wo…
Emerging Security Challenges of Large Language Models
Herve Debar, Sven Dietrich, Pavel Laskov +2
Large language models (LLMs) have achieved record adoption in a short period of time across many different sectors including high importance areas such as education [4] and healthc…