PARTREP: Learning What to Repeat for Decoder-only LLMs

Researchers have introduced PARTREP, a method designed to balance information flow in decoder-only large language models by identifying and strategically repeating key tokens. This approach addresses the limitation where later tokens in a sequence possess more contextual depth than earlier ones, potentially improving the model's overall reasoning and consistency.