dailyai.report

Researchers at arXiv argue that current language models are limited by data scarcity, historical bias, and human‑designed pipelines. They propose a framework for continual self‑improvement that reduces fine‑tuning inefficiencies, expands knowledge acquisition, and unlocks new training algorithms.