2 papers
cs.LG2025
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…
cs.CL2025
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…