3 papers
cs.LG2026
Behemoth: Benchmarking Unlearning in LLMs Using Fully Synthetic Data
Eugenia Iofinova, Dan Alistarh
As artificial neural networks, and specifically large language models, have improved rapidly in capabilities and quality, they have increasingly been deployed in real-world applica…
cs.CL2025
Position: It's Time to Act on the Risk of Efficient Personalized Text Generation
Eugenia Iofinova, Andrej Jovanovic, Dan Alistarh
The recent surge in high-quality open-source Generative AI text models (colloquially: LLMs), as well as efficient finetuning techniques, have opened the possibility of creating hig…
cs.CL2025
Panza: Design and Analysis of a Fully-Local Personalized Text Writing Assistant
Armand Nicolicioiu, Eugenia Iofinova, Andrej Jovanovic +6
The availability of powerful open-source large language models (LLMs) opens exciting use-cases, such as using personal data to fine-tune these models to imitate a user's unique wri…