2025
Expanding before Inferring: Enhancing Factuality in Large Language Models through Premature Layers Interpolation
EMNLP 2025
Large Language Models (LLMs) demonstrate remarkable capabilities in text understanding and generation. However, their tendency to produce factually inconsistent outputs—commonly referred to as “hallucinations”—remains a critical challenge. Existing approaches, such as retrieval-based and inference-t