2025
Data Doping or True Intelligence? Evaluating the Transferability of Injected Knowledge in LLMs
EMNLP 2025
As the knowledge of large language models (LLMs) becomes outdated over time, there is a growing need for efficient methods to update them, especially when injecting proprietary information. Our study reveals that comprehension-intensive fine-tuning tasks (e.g., question answering and blanks) achieve