4 citations · 5 across the 10 of their papers we have counts for
5 papers · 1 filter
When AI Takes the Couch: Psychometric Jailbreaks Reveal Internal Conflict in Frontier Models
Afshin Khadangi, Hanna Marxen, Amir Sartipi +2
Frontier language models increasingly participate in conversations about distress and mental health, yet the mechanisms that generate anthropomorphic self narratives remain unclear…
Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning
Afshin Khadangi, Amir Sartipi, Igor Tchappi +2
The tension between data privacy and model utility has become the defining bottleneck for the practical deployment of large language models (LLMs) trained on sensitive corpora incl…
KG-HTC: Integrating Knowledge Graphs into LLMs for Effective Zero-shot Hierarchical Text Classification
Qianbo Zang, Christophe Zgrzendek, Igor Tchappi +2
Hierarchical Text Classification (HTC) involves assigning documents to labels organized within a taxonomy. Most previous research on HTC has focused on supervised methods. However,…
Noise Augmented Fine Tuning for Mitigating Hallucinations in Large Language Models
Afshin Khadangi, Amir Sartipi, Igor Tchappi +1
Large language models (LLMs) often produce inaccurate or misleading content-hallucinations. To address this challenge, we introduce Noise-Augmented Fine-Tuning (NoiseFiT), a novel…
CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements
Afshin Khadangi, Amir Sartipi, Igor Tchappi +1
Art, as a universal language, can be interpreted in diverse ways, with artworks embodying profound meanings and nuances. The advent of Large Language Models (LLMs) and the availabi…