61 citations · 303 across the 45 of their papers we have counts for
47 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…
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…
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…
Shape error prediction in 5-axis machining using graph neural networks
Julia Huuk, Abheek Dhingra, Eirini Ntoutsi +1
This paper presents an innovative method for predicting shape errors in 5-axis machining using graph neural networks. The graph structure is defined with nodes representing workpie…
Unlocking LLMs: Addressing Scarce Data and Bias Challenges in Mental Health
Vivek Kumar, Eirini Ntoutsi, Pushpraj Singh Rajawat +2
Large language models (LLMs) have shown promising capabilities in healthcare analysis but face several challenges like hallucinations, parroting, and bias manifestation. These chal…