Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs

ArXi:2510.09885v5 Announce Type: replace-cross Large language models (LLMs) are often used in environments where facts evolve, yet factual knowledge updates via fine-tuning on unstructured text often suffer from 1) reliance on compute-heavy paraphrasing augmentation and 2) the reversal curse. Recent studies show diffusion large language models (dLLMs) require fewer