4 papers
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…
Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting
Timothée Hornek Amir Sartipi, Igor Tchappi, Gilbert Fridgen
Accurate electricity price forecasting (EPF) is crucial for effective decision-making in power trading on the spot market. While recent advances in generative artificial intelligen…
Towards Effective E-Participation of Citizens in the European Union: The Development of AskThePublic
Nils Messerschmidt, Kilian Sprenkamp, Amir Sartipi +4
E-participation platforms are an important asset for governments in increasing trust and fostering democratic societies. By engaging public and private institutions and individuals…
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…