4 papers
QR-Erase: Efficient Subspace-Based Machine Unlearning with Layer Localization
Tyler Lizzo, Larry Heck
Machine unlearning seeks to remove targeted information from trained models without requiring costly retraining. Existing optimization-based methods often degrade unrelated capabil…
Unlearning in LLMs: Methods, Evaluation, and Open Challenges
Tyler Lizzo, Larry Heck
Large language models (LLMs) have achieved remarkable success across natural language processing tasks, yet their widespread deployment raises pressing concerns around privacy, cop…
Evaluating Cross-Lingual Unlearning in Multilingual Language Models
Tyler Lizzo, Larry Heck
We present the first comprehensive evaluation of cross-lingual unlearning in multilingual LLMs. Using translated TOFU benchmarks in seven language/script variants, we test major un…
LEGO: Language Model Building Blocks
Shrenik Bhansali, Alwin Jin, Tyler Lizzo +1
Large language models (LLMs) are essential in natural language processing (NLP) but are costly in data collection, pre-training, fine-tuning, and inference. Task-specific small lan…