Relearn: Machine Unlearning Framework for LLMs
A novel framework for machine unlearning in large language models that enables effective removal of specific knowledge while preserving model performance through a learning-based approach.
Portfolio
Dynamic Correction Decoding for Hallucination Mitigation
A decoding strategy for multimodal large language models that leverages visual information to detect and correct hallucinations during text generation, significantly reducing factual errors.